Methods for detecting, diagnosing and treating human renal cell carcinoma

ABSTRACT

Gene expression profiling and hierarchical clustering analysis readily identify differential gene expressions in normal renal epithelial cells and renal cell carcinomas. Genes identified by this analysis would be useful for diagnosis, prognosis and development of targeted therapy for the prevention and treatment of conventional renal cell carcinoma.

CROSS-REFERENCE TO RELATED APPLICATION

This is a continuation application under 35 U.S.C. §120 of pending nonprovisional application U.S. Ser. No. 10/938,973, filed Sep. 10, 2004, which claims benefit of provisional application U.S. Ser. No. 60/539,838, filed Jan. 28, 2004, now abandoned, and of provisional application U.S. Ser. No. 60/502,038, filed Sep. 10, 2003, now abandoned, the entirety of all of which are hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to the field of cancer research. More specifically, the present invention relates to gene expression profiling for human renal cell carcinoma.

2. Description of the Related Art

Renal cell carcinoma (RCC) represents a major health issue. The American Cancer Society predicts 31,900 new cases will be diagnosed in the United States alone in the year 2003, with 11,900 people dying of the disease. When clinically localized or even locally advanced, renal cell carcinoma can be surgically resected for cure using a variety of approaches. With metastatic progression, however, renal cell carcinoma is incurable, and existing systemic therapies are largely ineffective in impacting disease response or patient survival. The lack of effective systemic therapy for metastatic renal cell carcinoma is, in part, due to a fundamental lack of understanding of the molecular events that result in cellular transformation, carcinogenesis, and progression in human kidney.

The advent of gene array technology has allowed classification of disease states at molecular level by examining changes in all mRNAs expressed in cells or tissues. Gene expression fingerprints representing large numbers of genes may allow precise and accurate grouping of renal cell carcinoma. Moreover, large scale gene expression analysis have the potential of identifying a number of differentially expressed genes in renal cell carcinoma compare to normal renal epithelial cells. These genes or markers may further be tested for clinical utility in the diagnosis and treatment of renal cell carcinoma.

Thus, the identification of novel renal cell carcinoma markers to be used for detection, diagnosis and development of effective therapy against the disease remains a high priority. The prior art is deficient in understanding the molecular differences between renal cell carcinoma and normal renal epithelium. The present invention fulfills this need in the art by providing gene expression profiling for these two types of tissues.

SUMMARY OF THE INVENTION

The present invention identifies genes with a differential pattern of expression between different subtypes of renal cell carcinomas (RCC) and normal renal epithelium. These genes and their products can be used to develop novel diagnostic and therapeutic markers for the treatment of renal cell carcinomas.

Genomic profiling of conventional renal cell carcinoma tissues and patient-matched normal kidney tissue samples was carried out using stringent statistical analyses (ANOVA with full Bonferroni corrections). Subtypes of renal cell carcinoma include stage I, II, III, and IV (reflecting differences in tumor size, lymph node and organ metastasis), stage I papillary renal cell carcinoma, and benign oncocytoma. Hierarchical clustering of the expression data readily distinguished normal tissue from renal cell carcinomas. The identified genes w ere verified by real-time FCR and immunohistochemical analyses.

Different subtypes of conventional renal cell carcinomas can be diagnosed either by drawing blood and identifying secreted gene products specific to renal cell carcinoma or by doing a biopsy of the tissue and then identify specific genes that are altered when renal cell carcinoma is present. An example of when this may be especially important is in distinguishing the deadly conventional renal cell carcinomas (account for 85% of all renal cell carcinomas) from renal oncocytoma (benign renal cell carcinoma) as well as identifying the histologic subtypes of papillary and sarcomatoid renal cell carcinoma. Identification of specific genes will also help in determining which patients will have a good prognosis verses that of a poor prognosis. In addition, subsets of genes identified in the present invention can be developed as targets for therapies that could cure, prevent, or stabilize the disease. Thus, results from the present invention could be used for diagnosis, prognosis, and development of therapies to treat or prevent renal cell carcinoma.

In one embodiment, there are provided methods of detecting conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein. In another embodiment, conventional or clear cell renal cell carcinoma is detected based on decreased expression of type III TGF-β receptor.

In yet another embodiment, there are provided methods of detecting stage I conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

The present invention also provides methods of detecting stage II conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

The present invention also provides methods of detecting papillary renal cell carcinoma or benign oncocytoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

In another embodiment, there is provided a method of targeting conventional or clear cell renal cell carcinoma cells based on generating antibodies or small molecules directed against a cell surface molecule over-expressed in conventional renal cell carcinoma cells.

In yet another embodiment, there is provided a method of treating conventional or clear cell renal cell carcinoma by replacing down-regulated tumor suppressor gene in conventional renal cell carcinoma.

Other and further aspects, features, and advantages of the present invention will be apparent from the following description of the presently preferred embodiments of the invention. These embodiments are given for the purpose of disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows hierarchical clustering of genes expressed in normal renal cortex (12 patient tissue samples) verse stage I conventional renal cell carcinoma (6 patient tissue samples). Red indicates that a gene is highly expressed and green is indicative of low expression. Four hundred eighty eight genes were depicted in FIG. 1A. FIG. 1B shows hierarchical clustering of genes expressed in normal renal cortex (12 patient tissue samples) verse stage II conventional renal cell carcinoma (6 patient tissue samples). Red indicates that a gene is highly expressed and green is indicative of low expression. Six hundred twenty eight genes were depicted in FIG. 1B. FIG. 1C shows hierarchical clustering of genes selected from a Venn analysis in which the chosen genes were expressed in common in both stage I and II at a 99% confidence level. One hundred eighty eight genes were depicted in FIG. 1C. C, cancer cells; N, normal cells; S1, stage 1; S2, stage 2.

FIG. 2 shows TGF-β1 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR TGF-β1 mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 3 shows TGF-α mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-α mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 4 shows adrenomedulin mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. Adrenomedulin mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts. FIG. 5 shows TGF-β2 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-β2 mRNA levels were not altered between normal and tumor matched samples.

FIG. 6 shows TGF-β3 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-β3 mRNA levels were not altered between normal and tumor matched samples.

FIG. 7 shows tumor suppressor gene Wilms Tumor 1 (WT1) mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. WT1 mRNA levels were down-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 8 shows von Hippel Lindau mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. A small percentage of tumor tissues demonstrated attenuated von Hippel Lindau mRNA levels when compared to matched normal tissue

FIG. 9 shows calbindin mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. Calbindin mRNA was completely lost in all stage I renal cell carcinoma. p<0.05 compared to matched control. *Stage I tumor: 0±0; stage III tumor: 0.0009±0.0004; stage IV tumor: 0.003±0.0004/

FIG. 10 shows MUC1 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. MUC1 mRNA levels were down-regulated in all tumor tissues as early as stage I. *p<0.05 compared to matched control.

FIGS. 11A-11B show stepwise loss of type III αreceptor (TBR3) and type II TGF-β receptor (TBR2) mRNA expression during renal cell carcinogenesis and progression in patient tissue samples. FIG. 11A shows gene array data from 10 patients—five diagnosed with localized renal cell carcinoma and five with metastatic disease. ‘+’ (P<0.05) indicates statistical difference for TBR3 mRNA levels as compared to normal tissue and ‘*’ (P<0.28) indicates statistical difference for TBR2 mRNA levels as compared to normal controls. Data are expressed as mean±s.e. FIG. 11B shows real-time RT-PCR verification of TBR1, TBR2, and TBR3 mRNA levels of tissue samples described in FIG. 11A. Data are expressed as mean±s.d.

FIG. 12 shows immunohistochemistry of patient tissue demonstrating loss of type III αreceptor (TBR3) expression (top row) in all tumors, loss of type II αreceptor (TBR2) expression (middle row) in patients diagnosed with metastatic tumors, and no change in type I αreceptor (TBR1) protein expression (bottom row).

FIG. 13 demonstrates down-regulation of TGF-β-regulated genes in human tumor tissues by real-time PCR. Genes known to be up-regulated by αare suppressed in tumor tissues. Down-regulation of collagen IV type 6, fibulin 5, and connective tissue growth factor (CTGF) mRNA in tumor tissues were compared to matched normal tissue controls. Values were normalized to 18 s mRNA. Each matching tumor value was compared to its respective normal control. The mean±s.d. was calculated for each sample group with n values of 10-15 matched samples.

FIGS. 14A-14B show tumor cell lines that lose type III αreceptor (TBR3) and type I TGF-β receptor (TBR2) expression. FIG. 14A shows semi-quantitative RT-PCR measurements of mRNA levels of TBR1, TBR2, and TBR3 for UMRC3, UMRC6 and normal renal epithelial (NRE) cells. FIG. 14B shows immunohistochemistry of protein expression for TBR1, TBR2, and TBR3 (×40 magnification).

FIGS. 15A-15B show loss of type III TGF-β receptor (TBR3) and type II αreceptor (TBR2) expression in renal tumor cell lines correlate with loss of TGF-β-regulated growth inhibitory and transcriptional responses. FIG. 15A shows cell proliferation was inhibited as assessed by DNA content 3 days after αtreatment. Percent of each respective untreated control was used for comparisons. Transient transfection using 3TP/Ix along with a renilla luciferase control demonstrates loss of responsiveness to 2 ng/ml TGF-β1 with loss of TGF-β receptor expression (FIG. 15B). Firefly luciferase activity was normalized using the ratio of firefly luciferase/renilla luciferase. Data are expressed as mean±s.d.

FIG. 16A demonstrates RT-PCR derived mRNA expression of type III αreceptor (TBR3), type II αreceptor (TBR2), and type I αreceptor (TBR1) in UMRC3 cells and cells stably transfected with TBR2 and TBR3. FIG. 16B shows UMRC3 cells stably transfected with type II TGF-β receptor (UMRC3+TBR2) or type II and type III TGF-β receptor (UMRC3+TBR2+TBR3) demonstrated attenuated cell proliferation following the administration of exogenous TGF-β1 as compared to that of UMRC3 cells. FIG. 16C shows UMRC3 cells, UMRC3+TBR2 cells, and UMRC3+TBR2+TBR3 stable cell lines transfected with 3TP/lux were treated with or without TGF-β and examined for luciferase activity. FIG. 16D shows real-time PCR measuring mRNA levels for collagen IV type 6 in UMRC3, UMRC3+TBR2 cells, and UMRC3+TBR2+TBR3 cells in the presence of 2 ng/ml TGF-β1 for 24 h. FIG. 16E shows colony formation assay demonstrates that UMRC3+TBR2+TBR3 cells have completely lost anchorage-independent growth, while attenuated growth in UMRC3+TBR2 cells occurs as compared to that of UMRC3 cells. The number of colonies were stained and counted after 45 days of growth. Data are expressed as mean±s.d.

FIG. 17A shows growth inhibition after re-expressing human type III TGF-β receptor (TBR3) in UMRC3 cells. UMRC3 cells were stably transfected with TBR3 or infected using an adenoviral vector expressing TBR3. Cells were plated in culture dishes at 20,000 cells/well. Cell number was determined at the indicated times using a Coulter cell counter. FIG. 17B shows RT-PCR data demonstrating the mRNA expression levels of type I, II, or III TGF-β receptors (TBR1, TBR2, TBR3) in UMRC3 cells in the presence or absence of the adenoviral vector expressing TBR3. Unmodified UMRC3 cells only express TBR1.

FIG. 18 shows re-expression of human type II or III TGF-β receptors (TBR2 or TBR3) inhibits tumor growth in nude mice. One million UMRC3 cells stably transfected with human type II or type III TGF-β receptors were implanted into nude mice ectopically and tumor growth was measured weekly. Tumor volume (mm³) was calculated by width×length×height×0.5236.

FIG. 19 shows hierarchical clustering of genes expressed in normal renal cortex verse stage I papillary renal cell carcinoma. Red indicates that a gene is highly expressed and green is indicative of low expression.

FIG. 20 shows hierarchical clustering of genes expressed in normal renal cortex verse benign oncocytoma. Red indicates that a gene is highly expressed and green is indicative of low expression.

FIG. 21 shows venn analysis of gene distribution among stage I renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma.

FIG. 22 shows venn analysis of gene distribution among stage II renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma.

DETAILED DESCRIPTION OF THE INVENTION

High-throughput technologies for assaying gene expression, such as high-density oligonucleotide and cDNA microarrays, offer the potential to identify clinically relevant genes differentially expressed between normal and tumor cells. The present invention discloses a genome-wide examination of differential gene expression between renal cell carcinomas (RCC) and normal renal epithelial cells.

Currently, there are no proven molecular markers useful clinically for the diagnosis, staging, or prognosis of sporadic renal cell carcinoma. The present invention detects genes that have differential expression between renal cell carcinomas and normal renal epithelial cells. The known function of some of these genes may provide insight into the biology of renal cell carcinomas while others may prove to be useful as diagnostic or therapeutic markers against renal cell carcinomas. Subtypes of renal cell carcinomas disclosed herein include stage I, II, III, and IV renal cell carcinomas (reflecting differences in tumor size, lymph node and organ metastasis), stage I papillary renal cell carcinoma, and benign oncocytoma.

The present invention provides methods of detecting conventional renal cell carcinoma based on determining the expression level of a number of genes that are found to have 2-fold or higher differential expression levels between tumor and normal tissue. In general, biological samples (e.g. tissue samples, serum samples, urine samples, saliva samples, blood samples or biopsy samples) are obtained from the individual to be tested and gene expression at RNA or protein level is compared to that in normal tissue. The normal tissue samples can be obtained from the same individual who is to be tested for renal cell carcinoma. It will be obvious to one of ordinary skill in the art that gene expression can be determined by DNA microarray and hierarchical cluster analysis, real-time PCR, RT-PCR, or northern analysis, whereas secreted gene products can be measured in blood samples by standard procedures.

In one embodiment, there is provided a method of detecting conventional or clear cell renal cell carcinoma based on differential expression of one or more of the following genes or proteins: TGF-β1, TGF-α, adrenomedulin, fibroblast growth factor 2 (FGF2), vascular epidermal growth factor (VEGF), osteonectin, follistatin like-3, inhibin beta A, spondin 2, chemokine X cytokine receptor 4 (CXCR4), fibronectin, neuropilin 1, frizzled homolog 1, insulin-like growth factor binding protein 3, laminin alpha 3, integrin beta 2, semaphorins 6A, semaphorins 5B, semaphorins 3B, caspase 1, sprouty 1, CDH16, PCDH9, compliment component 1-beta, compliment component 1-alpha, compliment component 1-gamma, CD53, CDW52, CD163, CD14, CD3Z, CD24, RAP1, angiopoietin 2, cytokine knot secreted protein, MAPKKKK4, 4-hydroxyphenylpyruvate dioxygenase, pyruvate carboxyknase 2, 11-beta-hydroxysteroid dehydrogenase 2, GAS1, CDKN1, nucleolar protein 3, interferon induced protein 44, NR3C1, vitamin D receptor, hypothetical protein FLJ14957 (Affy#225817_at), metallothionein 2A, metallothionein-If gene, metallothionein 1H, secreted frizzled related protein 1, connective tissue growth factor, and epidermal growth factor.

In another embodiment, there is provided a method of detecting conventional renal cell carcinoma by examining the expression level of type III TGF-β receptor, wherein decreased expression of type III TGF-b receptor indicates the presence of renal cell carcinoma. In general, the expression level of type III TGF-β receptor can be determined at the mRNA or protein level.

The present invention also provides methods of detecting stage I conventional renal cell carcinoma, stage II conventional renal cell carcinoma, stage I papillary renal cell carcinoma, or benign oncocytoma based on over-expression or down-regulation of a number of genes identified in the present invention. The present invention discloses a number of genes that are up- or down-regulated specifically in these subtypes of renal cell carcinoma. Determining the expression levels of these genes would provide specific diagnosis for these different subtypes of renal cell carcinoma.

For example, stage I conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 1, (ii) down-regulation of one or more genes listed in Table 2, or (iii) over-expression of one or more genes listed in Table 1 and down-regulation of one or more genes listed in Table 2. Similarly, stage II conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 3, (ii) down-regulation of one or more genes listed in Table 4, or (iii) over-expression of one or more genes listed in Table 3 and down-regulation of one or more genes listed in Table 4.

The present invention also discloses a number of genes that are up- or down-regulated in both stage I and stage II conventional renal cell carcinoma (Tables 5 and 6 respectively). These genes would also provide diagnosis for stage I or stage II conventional renal cell carcinoma. Hence, stage I or stage II conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 5, or (ii) down-regulation of one or more genes listed in Table 6.

In another embodiment, stage I papillary renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 8, (ii) down-regulation of one or more genes listed in Table 9, or (iii) over-expression of one or more genes listed in Table 8 and down-regulation of one or more genes listed in Table 9.

In yet another embodiment, benign oncocytoma can be detected based on (i) over-expression of one or more genes listed in Table 10, (ii) down-regulation of one or more genes listed in Table 11, or (iii) over-expression of one or more genes listed in Table 10 and down-regulation of one or more genes listed in Table 11.

In still yet another embodiment, there are provided methods of utilizing genes over-expressed on the cell surface of renal carcinoma tissue to develop antibodies or other small molecules for the purpose of specifically targeting the renal tumor cells. The present invention discloses a number of genes that are up-regulated in stage I renal cell carcinoma (RCC), stage II RCC tumor, stage I papillary RCC, and benign oncocytoma. Antibodies or small molecules directed against proteins encoded by these genes can be linked with a therapeutic drug to deliver drug to the tumor tissue, or be linked with dye, nanoparticle or other imaging agents for cancer imaging. Some of the novel genes identified herein for the first time include, but are not limited to, the following genes: calcitonin receptor-like (206331_at; 210815_s_at); receptor (calcitonin) activity modifying protein 2 (RAMP2; 205779_at); endothelin receptor type B (206701_x_at); beta 2 integrin (202803_s_at); alpha 5 integrin (201389_at); chemokine X cytokine receptor 4 (CXCR4); fibronectin; neuropilin 1 (212298_at; 210510_s_at); CD24; CD14; Cd163; CD53; Compliment Componenet 1-beta, 1-alpha, and 1-gamma; CDH4; integrin beta2; ADAM28; FK506 binding protein; collagen Valpha2; tumor necrosis factor receptor superfamily, member 6; tumor necrosis factor receptor superfamily, member 5; tumor necrosis factor (ligand) superfamily, member 13b; tumor necrosis factor receptor superfamily, member 12A; and the FGF receptor.

In another embodiment, there is provided a method of treating conventional or clear cell renal cell carcinoma. The method involves replacing tumor suppressor genes (e.g., via gene therapy) whose expression is down-regulated in tumor tissues or introducing a molecule that induces the down-regulated gene to be re-expressed in the tumor. The present invention discloses a number of genes that are down-regulated in stage I renal cell carcinoma (RCC), stage II RCC tumor, stage I papillary RCC, and benign oncocytoma. Some examples of down-regulated genes identified in stage I and/or II RCC tumors include, but are not limited to, CDKN1, secreted frizzled related protein 1, semaphoring 6D, semaphoring 3B, CDH16, TNF alpha, calbindin D28, defensin betal, beta-catenin interacting protein 1, GAS1, vitamin D receptor, Kruppel-like factor 15. This method of treatment can be combined with other therapies to provide combinatorial therapy.

The genes that are found to have altered expression in stage I and stage II renal cell carcinoma would also be useful for determining patient prognosis. These genes or gene products (i.e., proteins) would have the unique characteristic of being altered in tumor verses normal samples in a subset of patients. For example, basic transcription element binding protein 1 is down-regulated in 7 out of 12 renal cell carcinoma tumors. Other examples include CD164, decreased 5/12; Map kinase kinase kinase 7, increased 6/12; Endoglin, increased 7/12; SERPIN A1, increased 6/12; Metalloprotease 11 (MMP11), increased 7/12; Integrin 3 alpha, increased 4/12; carbonic anhydrase II, decreased 7/12; protein tyrosine kinase 2, increased 4/12; fibroblast growth factor 11, increased 6/12; fibroblast growth factor 2, increased 7/12; VEGF B, increased 5/12.

Moreover, the levels of change may be a useful determinant of patient outcome and/or rationale for strategy of treatment course. An example of this is found for chemokine (C—X—C motif) ligand 14 (CXCL14, 222484_s_at). Six patients with stage I and six patients with stage II renal cell carcinoma were analyzed by genomic profiling. A patient with stage I renal cell carcinoma has CXCL14 mRNA expression levels of 19862 and 24.49 in his normal tissue and tumor tissue respectively. This patient would be predicted to have a poor prognosis or poor response to therapy based upon this result along with other gene predictors. On the other hand, a patient with stage II RCC has CXCL14 mRNA expression levels of 20435 and 18557 in his normal tissue and tumor tissue respectively. This patient would be predicted to have a good prognosis and good response to chemotherapy.

The following examples are given for illustrating various embodiments of the invention and are not meant to limit the present invention in any fashion. One skilled in the art will appreciate readily that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those objects, ends and advantages inherent herein. Changes therein and other uses which are encompassed within the spirit of the invention as defined by the scope of the claims will occur to those skilled in the art.

EXAMPLE 1 Tissue Banking

Renal tissue (normal and tumor) was transported to a sterile hood on ice and under sterile conditions. Tissue was dissected under the direction of a pathologist. The tissue was frozen in liquid nitrogen for isolation of RNA, DNA, and protein or processed to establish primary cell cultures. The tissue was fixed in formalin for immunohistochemistry and in situ hybridization and RNAlater (Ambion) for RNA isolation. Primary normal renal epithelial (NRE) cell cultures were established using standard collagenase/Dnase techniques to digest tissue and isolate single cells. NREs were easily isolated and grew well in culture for up to 10 passages. These cells were further analyzed for homogeneity with regard to epithelial population using appropriate immunohistochemical markers such as vimentin, cytokeratin, and megalin.

EXAMPLE 2 Genomic Gene Array And Microarray Data Analysis

Gene expression profiling was performed using Affymetrix HU95A oligonucleotide gene arrays (>12,600 genes) or HG-U133 A&B GeneChip® oligonucleotide microarrays (33,000+ probe sets). Total RNA (Trizol®, Ambion) was extracted from patient-matched normal renal cortex and tumor tissue from patients diagnosed with local disease confined to the kidney. Alternatively, the investigators analyzed metastatic disease defined by lesions in lymph nodes, adrenal, or other organs. Data were analyzed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0®, and hierarchical cluster analysis using Spotfire®. Procedure that were used to identify altered expression of large sets of genes, as well as other issues concerning microarray analyses can be found in a recent review article by Copland et al. (2003).

EXAMPLE 3 Real-Time PCR

Applied Biosystems' assays-by-design or assays-on-demand 20× assay mix of primers and TaqMan® MGB probes (FAM® dye-labeled) for all target genes and predeveloped 18S rRNA (VIC® dye-labeled probe) TaqMan® assay reagent for internal control were used for real-time PCR measurements. These assays were designed to span exon-exon junctions so as not to detect genomic DNA and all primers and probes sequences were searched against the Celera database to confirm specificity. Validation experiments were performed to test the efficiency of the target amplification and the efficiency of the reference amplification. All absolute values of the slope of log input amount versus DC_(T) is less than 0.1.

Separate tubes (singleplex) for one-step RT-PCR was performed with 50 ng RNA for both target genes and endogenous controls using TaqMan® one-step RT-PCR master mix reagent kit (Applied Biosystems). The cycling parameters for one-step RT-PCR were: reverse transcription 48° C. for 30 min, AmpliTaq® activation 95° C. for 10 min, denaturation 95° C. for 15 s, and annealing/extension 60° C. for 1 min (repeat 40 times) on ABI7000®. Duplicate C_(T) values were analyzed with Microsoft Excel® using the comparative C_(T)(DDC_(T)) method as described by the manufacturer (Applied Biosystems). The amount of target (2^(−DDCT)) was obtained by normalizing to an endogenous reference (18smRNA) and relative to a calibrator (normal tissue).

EXAMPLE 4 Immunohistochemical Analyses of Protein Expression

For immunohistochemical analyses of type I TGF-β receptor (TBR1), type II TGF-β receptor (TBR2), and type Ill TGF-β receptor (TBR3) expression, patient-matched normal renal and tumor tissue samples were fixed in 10% neutral-buffered formalin and embedded in paraffin blocks. Consecutive sections were cut 5 um thick, deparaffinized, hydrated, and immunostained using antibodies recognizing human TBR1, TBR2, and TBR3 (1:100; Santa Cruz Biotechnology). Biotinylated secondary antibody (1:600; Santa Cruz Biotechnology) was detected using avidin-biotin-peroxidase detection according to the manufacturer's instructions (Vectastatin Elite ABC kit; Vector Lab). All slides were lightly counterstained with hematoxylin before dehydration and mounting.

For cell lines, cells were plated on glass coverslips in wells. Prior to the detection of TGF-β receptor expression as described above, cells were fixed onto the coverslips with 3% formalin.

EXAMPLE 5 Gene Expression Profiling of Renal Cell Carcinoma

Gene expression profiling was performed using Affymetrix oligonucleotide gene arrays. RNA was extracted from patient-matched normal renal cortical and tumor tissues from patients diagnosed with localized and metastatic renal cell carcinoma. Data were analyzed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0®, and hierarchical cluster analysis using Spotfire® (reviewed in Copland et al., 2003).

A primary goal of microarray analysis is to discover hidden patterns of differential expression within a large data field. Normal renal cortical and primary tumor tissue with no metastasis were collected from patients diagnosed with local disease. Normal tissue, primary tumor, and metastatic tissue were also collected from patients diagnosed with metastatic disease. Comparison of patient-matched normal and tumor tissue allowed for the discovery of changes in mRNA levels between normal and tumor tissue, as well as local and metastatic disease.

Heatmaps with two-way dendograms depicting genes specifically altered in tumor tissue as compared to normal renal cortex are shown in FIG. 1. FIG. 1A shows hierarchical clustering of genes expressed in normal renal cortex verses stage I conventional renal cell carcinoma. FIG. 1B shows hierarchical clustering of genes expressed in normal renal cortex verses stage II renal cell carcinoma. FIG. 1C shows hierarchical clustering of genes selected from a Venn analysis in which the chosen genes were expressed in common in both stage I and II at a 99% confidence level.

TGF-β1, TGF-α and adrenomedulin mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts (FIGS. 2-4), whereas TGF-β2 and TGF-β3 mRNA levels were not altered between normal and tumor matched samples (FIGS. 5-6).

Tumor suppressor gene Wilms Tumor 1 (WT1) was down-regulated in all stages of renal cell carcinoma (FIG. 7). A small percentage of tumor tissues demonstrated attenuated von Hippel Lindau mRNA levels when compared to matched normal tissue (FIG. 8). Calbindin mRNA was completely lost (FIG. 9) while MUC1 was greatly attenuated in stage I renal cell carcinoma (FIG. 10).

The present analysis identifies 278 genes that were up-regulated in stage I renal cell carcinoma, whereas 380 genes were up-regulated in stage II renal cell carcinoma. Among these genes, 82 were up-regulated in both stages I and II renal cell carcinoma. One hundred fifty nine genes were down-regulated in stage I renal cell carcinoma, whereas 195 genes were down-regulated in stage II RCC. Among these genes, 82 were down-regulated in both stage I and II renal cell carcinoma.

Genes over-expressed and down-regulated in stage I renal cell carcinoma are listed in Table 1 and Table 2 respectively. Genes over-expressed and down-regulated in stage I renal cell carcinoma are listed in Table 3 and Table 4 respectively. Genes over-expressed in both stage I and II renal cell carcinoma are listed in Table 5. Genes down-regulated in both stage I and II renal cell carcinoma are listed in Table 6.

TABLE 1 Genes With Up-Regulated Expression In stage I Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM004356.1 CD81 NM004079.1 CTSS NM002293.2 LAMC1 NM001784.1 CD97 NM000980.1 RPL18A AF151853.1 PREI3 AK002091.1 MGEA5 NM000491.2 C1QB NM005721.2 ACTR3 BC000125.1 TGFB1 NM002668.1 PLP2 NM004520.1 KIF2 NM021038.1 MBNL NM000321.1 RB1 AF070656.1 YME1L1 NM012262.2 HS2ST1 NM021029.1 RPL36A NM000560.1 CD53 NM002945.1 RPA1 NM005502.1 ABCA1 NM002480.1 PPP1R12A AF285167.1 ABCA1 NM001349.1 DARS BG170541 MET NM005496.1 SMC4L1 NM021642.1 FCGR2A AW163148 MARCKS BE967532 KIAA0220 NM002356.4 MARCKS NM006526.1 ZNF217 M68956.1 MARCKS NM000570.1 FCGR3B AI589086 LAPTM5 N26005 PPP1R3C NM006762.1 LAPTM5 NM006153.1 NCK1 NM014267.1 SMAP NM001549.1 IFIT4 NM000235.1 LIPA NM003141.1 SSA1 NM000176.1 NR3C1 NM014705.1 KIAA0716 NM005737.2 ARL7 NM005197.1 CHES1 NM005737.2 ARL7 NM002907.1 RECQL BC001051.1 ARL7 U43328.1 CRTL1 NM006169.1 NNMT NM017925.1 FLJ20686 NM005862.1 STAG1 NM006773.2 DDX18 AI356412 LYN U20350.1 CX3CR1 NM002350.1 LYN NM005761.1 PLXNC1 BG107456 TRIP-Br2 NM004834.1 MAP4K4 NM021913.1 AXL NM021644.1 HNRPH3 NM002194.2 INPP1 NM006640.1 MSF NM019058.1 RTP801 NM004180.1 TANK NM002110.1 HCK AW148801 NAP1L1 NM030755.1 TXNDC AB011118.1 KIAA0546 NM030984.1 TBXAS1 AU145005 SP3 NM014350.1 GG2-1 N80918 CG018 BC001312.1 P5 BF439472 ATP11A U14990.1 RPS3 BE968801 RPL35A D83043.1 HLA-B AI985751 NAP1L1 AI888672 NAP1L1 AI735692 LST1 BC002387.1 NAP1L1 AA995910 ALOX5 M60334.1 HLA-DRA M12679.1 HUMMHCW1A AF161522.1 C3orf4 AL133053.1 FLJ23861 BG256677 IFI16 X03348.1 NR3C1 M26880.1 UBC AC005339 N/A U17496.1 PSMB8 AK024836.1 HLA-C AF141347.1 TUBA3 AC003999 SCAP2 L01639.1 CXCR4 AJ224869 CXCR4 NM005445.1 CSPG6 AL022067 PRDM1 AB030655.1 EFEMP2 AL110158.1 KIAA1078 AF165520.1 APOBEC3C S81916.1 N/A AF009670.1 ABCC3 M80469 N/A AF020314.1 CMRF-35H NM002860.1 PYCS BC001606.1 NCF2 NM020198.1 GK001 BC005352.1 GG2-1 NM016304.1 C15orf15 AF281030.1 HRIHFB2122 AA102574 BAZ1A BC001052.1 RECQL NM024844.1 PCNT1 L32610.1 HNRPH3 NM015938.1 CGI-07 M23612.1 RASA1 NM018200.1 HMG20A AF109683.1 LAIR1 NM025235.1 TNKS2 BC002841.1 HSA9761 NM015991.1 C1QA D29640.1 IQGAP1 NM016090.1 RBM7 L25259.1 CD86 NM024554.1 PGBD5 M60333.1 HLA-DRA NM017718.1 FLJ20220 U13698.1 CASP1 NM017923.1 FLJ20668 U90940.1 FCGR2C NM030921.1 DC42 M90685.1 HLA-G BC004470.1 ASC M90684.1 HLA-G AK021413.1 LARS M90686.1 HLA-G BF444916 FAD104 L22453.1 RPL3 BC004819.1 PLDN U01351.1 NR3C1 AF247167.1 AD031 U62824.1 HLA-C U39402.1 N/A L07950.1 HLA-B BC006112.1 DKFZP434B195 AF348491.1 CXCR4 BG388615 N/A NM003079.1 SMARCE1 AB033007.1 KIAA1181 BE646386 EXO70 BG250721 N/A AI972475 N/A AK024221.1 C40 AA195999 MAPK1 BF477658 N/A AL049397.1 N/A BG251556 KIAA1949 BE895685 KIAA0853 AB033091.1 KIAA1265 M82882.1 ELF1 AK024350.1 AMOTL1 AB020633.1 KIAA0826 NM018440.1 PAG AL031781 N/A AW500180 N/A BF209337 MGC4677 AW026543 N/A AI709406 N/A AI092770 N/A AI806905 N/A NM020679.1 AD023 AI392933 FLJ36090 AK024855.1 CTSS AH42096 N/A AK000119.1 N/A AL137430.1 N/A AW977527 PRDM1 AV724266 FLJ20093 BE671060 N/A BF589359 N/A AL037450 N/A AW084125 CAPZA1 AI401535 N/A N20927 RAP2B AV683852 N/A AI627666 LOC115548 BF055144 N/A AV726322 N/A AA352113 N/A AI697657 LANPL BF056209 N/A BF002625 N/A X60592 TMFRSF5 BF439533 N/A

TABLE 2 Genes With Down-Regulated Expression In stage I Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol L38487 ESRRA AK024386.1 GRHPR NM004415.1 DSP AL109716.2 N/A NM005327.1 HADHSC AK026411.1 ALDOB NM003321.1 TUFM M10943 N/A NM002084.2 GPX3 AW088547 N/A AI983043 N/A NM018049.1 GNRPX NM006066.1 AKR1A1 NM017900.1 AKIP NM006384.2 CIB1 NM006548.1 IMP-2 NM001685.1 ATP5J NM025135.1 KIAA1695 NM014652.1 IMP13 NM016458.2 LOC51236 NM013410.1 AK3 NM022128.1 RBSK NM016725.1 FOLR1 NM015974.1 CRYL1 NM021151.1 CROT NM013333.1 EPN1 NM005951.1 MT1H AA133341 C14orf87 NM005952.1 MT1X AF226732.1 NPD007 AL080102.1 N/A AF265439.1 MRPS15 BC000931.2 ATP5C1 AI743534 DKFZP564B1162 BC005398.1 DKFZP566D193 AB042647.1 B29 D87292.1 TST AL522667 ORF1-FL49 AU151428 IDH2 BG255416 KIAA0114 BC000109.1 ILVBL AF308301.1 MRPS26 AF333388.1 N/A BE408081 N/A NM005953.1 MT2A AL521634 FLJ32452 BF217861 N/A BF203664 MGC14288 AA594937 COBL BE645551 MGC39329 AW052179 COL4A5 AW193698 TGFBR3 AI884867 LOC155066 BF540829 N/A BF246115 N/A W72455 FLJ25476 AW028110 KIAA0500 AI457453 N/A AW242315 N/A BF056892 N/A AW080549 FUT3 AK024386.1 GRHPR AW149846 GPX3 AL109716.2 N/A AI038402 N/A AA442776 N/A AI051046 MGC4614 AI913600 N/A AI659456 N/A AW771908 N/A AW664964 N/A AI807887 N/A AI631895 SGK2 AW102941 N/A AI263078 FLJ31168 AW024656 N/A BF057634 HOXD8 AB002342 PRKWNK1 AA746038 GPR110

TABLE 3 Genes With Up-Regulated Expression In stage II Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM006096.1 NDRG1 NM002053.1 GBP1 NM006098.1 GNB2L1 NM000089.1 COL1A2 NM001780.1 CD63 NM021105.1 PLSCR1 NM003118.1 SPARC NM002467.1 MYC NM000291.1 PGK1 NM001284.1 AP3S1 NM003870.1 IQGAP1 AI825926 PLSCR1 AB032261.1 SCD NM014736.1 KIAA0101 NM002629.1 PGAM1 AF161461.1 LEPROTL1 NM003564.1 TAGLN2 NM014873.1 KIAA0205 NM000310.1 PPT1 AI005043 N/A NM003405.1 YWHAH NM000416.1 IFNGR1 U82164.1 MIC2 NM004172.1 SLC1A3 NM002305.2 LGALS1 NM004207.1 SLC16A3 NM001096.1 ACLY AI761561 HK2 NM002121.1 HLA-DPB1 Y09216.1 N/A NM021038.1 MBNL NM002922.1 RGS1 NM003651.1 CSDA NM005990.1 STK10 AV685920 CAPZA2 NM014863.1 GALNAC4S-6ST NM002654.1 PKM2 NM014737.1 RASSF2 NM001175.1 ARHGDIB NM000418.1 IL4R BC000182.1 ANXA4 BC000658.1 STC2 NM001153.2 ANXA4 NM003751.1 EIF3S9 NM001975.1 ENO2 NM002339.1 LSP1 NM006435.1 IFTTM2 NM004604.1 STX4A NM001387.1 DPYSL3 NM006404.1 PROCR BG398414 RPA1 AF275945.1 EVA1 NM004039.1 ANXA2 NM004221.1 NK4 NM005534.1 IFNGR2 NM004556.1 NFKBIE AL136877.1 SMC4L1 NM004688.1 NMI NM014876.1 KIAA0063 NM003332.1 TYROBP NM024830.1 FLJ12443 NM015136.1 STAB1 NM005505.1 SCARB1 NM006019.1 TCIRG1 NM003025.1 SH3GL1 NM004877.1 GMFG NM013285.1 HUMAUANTIG NM002317.1 LOX NM005720.1 ARPC1B NM025201.1 PP1628 AW157070 EGFR NM014800.1 ELMO1 NM002835.1 PTPN12 L41944.1 IFNAR2 NM004428.1 EFNA1 NM007268.1 Z39IG AW006290 SUDD NM006994.2 BTN3A3 NM014791.1 MELK AF091352.1 VEGF NM014882.1 KIAA0053 AB035482.1 ICB-1 NM003864.1 SAP30 Z24727.1 TPM1 NM001558.1 IL10RA M19267.1 TPM1 NM003264.1 TLR2 U13700.1 CASP1 NM014221.1 MTCP1 M27281.1 VEGF AV756141 CSF2RB BC005838.1 N/A AI123251 LCP2 BC005858.1 FN1 NM006433.2 GNLY BC005926.1 EVI2B NM000861.2 HRH1 BE513104 YARS NM001870.1 CPA3 AU147399 CAV1 NM003586.1 DOC2A AK023154.1 HN1L NM004271.1 MD-1 AK021757.1 KIAA0648 NM014932.1 NLGN1 H95344 VEGF NM014947.1 KIAA1041 AB023231.1 FNBP4 NM000647.2 CCR2 AL523076 N/A NM002562.1 P2RX7 NM030666.1 SERPINB1 NM006058.1 TNIP1 AB018289.1 KIAA0746 NM013447.1 EMR2 AW043713 SULF1 NM013416.1 NCF4 BE880591 EP400 NM001776.1 ENTPD1 AU158495 NOTCH2 NM020037.1 ABCC3 BE965029 N/A NM006135.1 CAPZA1 AL564683 CEBPB NM007036.2 ESM1 AA349595 RAB6IP1 AF034607.1 CLIC1 AI809341 PTPRC BC000915.1 PDLIM1 AW205215 KIAA0286 AL162068.1 NAP1L1 BE349017 HA-1 NM006947.1 SRP72 AF070592.1 HSKM-B L12387.1 SRI AI769685 CARS AF141349.1 N/A AI935123 LOC113146 AF263293.1 SH3GLB1 BG255188 N/A BC000389.1 TM4SF7 AI088622 PRKCDBP AF007162.1 CRYAB BE222709 N/A D38616.1 PHKA2 AW007573 DKFZP586L151 AV717590 ENTPD1 BG332462 N/A U87967.1 ENTPD1 AI862658 FEM1C H23979 MOX2 AI934469 KIAA0779 AF063591.1 MOX2 AB018345.1 KIAA0802 BC005254.1 CLECSF2 W87466 LOC92689 BC000893.1 H2BFT BE908217 ANXA2 L22431.1 VLDLR NM005615.1 RNASE6 AI741056 SELPLG BE300252 K-ALPHA-1 AF084462.1 RIT1 BF740152 MYO1F U62027.1 C3AR1 AV711904 LYZ M87507.1 CASP1 AW072388 N/A J04132.1 CD3Z AW190316 SHMT2 M31159.1 IGFBP3 NM005412.1 SHMT2 AF257318.1 SH3GLB1 NM006417.1 IFI44 BC001388.1 ANXA2 AL008730 C6orf4 AF130095.1 FN1 L16895 LOC114990 AF022375.1 VEGF Z21533.1 HHEX AA807529 MCM5 AK022955.1 DKFZp762L0311 AK026737.1 FN1 BF001267 N/A X14355.1 N/A AL558987 N/A AK025608.1 KIAA0930 AA577672 LOC151636 AF183421.1 RAB31 BE620734 ZAK NM002695.1 POLR2E AI937446 N/A AF288391.1 C1orf24 H99792 N/A NM003730.2 RNASE6PL BE966748 N/A NM016359.1 ANKT AI659418 MGC21854 NM014164.2 FXYD5 AI990891 DKFZp761K2222 NM022736.1 FLJ14153 AA827892 N/A NM021158.1 C20orf97 AL135264 N/A NM017792.1 FLJ20373 AI375753 N/A NM020142.1 LOC56901 AA573502 TAP2 NM016448.1 RAMP BG387557 CASP2 NM005767.1 P2Y5 AA554833 MAP1B NM020169.1 LXN AK026764.1 N/A NM022834.1 FLJ22215 AU146532 PDK1 NM018460.1 BM046 BE348597 N/A NM024629.1 FLJ23468 AL577758 LOC133957 NM018641.1 C4S-2 AI133452 FGG NM018295.1 FLJ11000 AU157224 N/A NM024576.1 FLJ21079 AI742057 N/A NM016582.1 PHT2 BE500942 N/A NM003116.1 SPAG4 N25631 RFXANK NM018454.1 ANKT AU145366 N/A NM018099.1 FLJ10462 AW270037 KIAA0779 NM007072.1 HHLA2 BF526978 N/A NM022445.1 TPK1 AW182575 N/A AW173623 TDE1 BF339831 MGC13114 AB044088.1 BHLHB3 AI056992 N/A AF043244.1 NOL3 BE222668 N/A AF133207.1 H11 BG165011 N/A AF313468.1 CLECSF12 AI188445 MGC14289 AA191576 NPM1 BE551416 HAK AI765383 KIAA1466 AI972498 a1/3GTP BC003654.1 SLC27A3 AW662189 N/A W60806 N/A AA142842 N/A AI335263 NETO2 BF939473 N/A AI378406 EGLN3 AI681260 N/A BC005400.1 FKSG14 AA551090 AP1S2 AI761520 CENTA2 AA045175 MS4A6A BC000771.1 TPM3 W05495 N/A BC000190.1 HSPC216 AI093231 N/A BC002776.1 SEMA5B AI565054 N/A AF132203.1 SCD AL553774 N/A BC006107.1 ARHGAP9 AK023470.1 MGC15875 AK024263.1 N/A AL157377 ENPP3 AK024846.1 SET7 AL139109 TEX11 BE878463 N/A AK025631.1 POLH AW304786 PTR4 AI873425 N/A AI769269 N/A BF541967 N/A AI935334 N/A AI686890 N/A BF437747 SAMHD1 AI936034 ITGA4 AW300953 N/A U88964 ISG20 H37811 N/A AJ243797 TREX1 AA603344 SAMHD1 D29642 KIAA0053 AA742310 N/A D87433 STAB1 AI248208 FLJ25804 AI129310 FLJ21562 AI962367 ECGF1

TABLE 4 Genes With Down-Regulated Expression In stage II Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM012248.1 SPS2 AB019695.1 TXNRD2 NM002300.1 LDHB M61900.1 PTGDS BC000306.1 HADHSC BF967998 N/A NM001640.2 APEH BF967998 N/A NM005875.1 GC20 AL526243 KIAA0446 NM003365.1 UQCRC1 NM000532.1 PCCB BF031714 HYA22 BE042354 LDHB NM005808.1 HYA22 AI587323 ATP5A1 AF113129.1 ATP6V1A1 AW195882 ATPW NM002402.1 MEST H71135 ADH6 NM006844.1 ILVBL AV659180 ALDOB NM004636.1 SEMA3B AK027006.1 TNRC9 NM002496.1 NDUFS8 AV693216 PLXNB1 NM006556.1 PMVK BG398937 N/A NM004255.1 COX5A NM002489.1 NDUFA4 NM002225.2 IVD NM003849.1 SUCLG1 NM004524.1 LLGL2 NM014019.1 HSPC009 AI950380 BCL7A NM024952.1 FLJ20950 AB020707.1 WASF3 NM014185.1 MOG1 NM000481.1 AMT NM018013.1 FLJ10159 NM012317.1 LDOC1 NM018373.1 SYNJ2BP NM006456.1 STHM NM014067.2 LRP16 NM006614.1 CHL1 NM013261.1 PPARGC1 NM015393.1 DKFZP564O0823 NM021963.1 NAP1L2 AV729634 DNAJC6 NM018658.1 KCNJ16 NM002628.1 PFN2 NM014553.1 LBP-9 NM003500.1 ACOX2 AF112204.1 ATP6V1H NM002655.1 PLAG1 AU145941 CDC14B NM004393.1 DAG1 AF061264.1 MGC4825 NM003026.1 SH3GL2 BF941492 FLJ10496 NM002010.1 FGF9 AI984229 HSPC121 NM014033.1 DKFZP586A0522 N71923 FLRT3 NM004868.1 GPSN2 BC005050.1 NICN1 BC000649.1 UQCRFS1 AF172327.1 N/A S69189.1 ACOX1 AF356515.1 HINT2 AF153330.1 SLC19A2 BE620739 RHOBTB3 AF094518.1 ESRRG BF435123 N/A M55575.1 BCKDHB AW149498 BTBD6 BE044480 MGC32124 AW024437 LOC118491 BF382393 N/A AW195353 N/A AV751731 PNKP BE044193 N/A U55984 N/A AI493303 FLJ31709 BF059512 DNER AI636080 N/A AK025934.1 Evi1 BF509031 ATP6V1G3 AL036088 SEMA6D AW242920 N/A BE964222 FLJ38482 BF002046 ANGPTL1 AW290940 N/A BF130943 N/A AL545998 N/A AW452631 N/A AW274874 N/A AI792937 N/A AI709389 N/A AI810572 N/A BF224092 MGC15854 BG165743 LOC112817 AU145805 N/A AW466989 N/A AW079843 MGC33338 R48991 N/A AW138815 N/A BF029215 MSI2 AW242286 N/A D21851 LARS2 AW025023 N/A Z83838 ARHGAP8 BE672659 N/A

TABLE 5 Genes With Up-Regulated Expression In both stage I & stage II Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM005566.1 LDHA NM014812.1 KIAA0470 NM000291.1 PGK1 AF208043.1 IFI16 NM001219.2 CALU BC002654.1 TUBB-5 NM002966.1 S100A10 BC006379.1 K-ALPHA-1 NM000034.1 ALDOA BC006481.1 K-ALPHA-1 NM002627.1 PFKP AF000426.1 LST1 NM006082.1 K-ALPHA-1 AF000424.1 LST1 AI922599 VIM BG500301 ITGB1 NM020474.2 GALNT1 AL516350 ARPC5 NM006406.1 PRDX4 M27487.1 HLA-DPA1 NM015344.1 LEPROTL1 M27487.1 HLA-DPA1 NM014755.1 TRIP-Br2 AW517686 ATP2B4 AI796269 NBS1 AL581768 K-ALPHA-1 NM005783.1 APACD AA524505 TSGA BF197655 N/A Z78330 ACTR3 NM001233.1 CAV2 Z78330 ACTR3 NM002845.1 PTPRM BG532690 ITGA4 NM014302.1 SEC61G AW005535 RAP2B U47924 CD4 NM007161.1 LST1 NM004106.1 FCER1G AK026577.1 ALDOA NM015474.1 SAMHD1 AI091079 SHC1 NM004915.2 ABCG1 AV713720 LST1 NM002432.1 MNDA NM021103.1 TMSB10 NM005565.2 LCP2 NM016337.1 RNB6 NM005531.1 IFI16 NM013260.1 HCNGP NM005849.1 IGSF6 NM021199.1 SQRDL NM002189.1 IL15RA NM018149.1 FLJ10587 NM004353.1 SERPINH1 NM016951.2 CKLF1 NM017760.1 FLJ20311 AB033038.1 FLJ10392 NM022349.1 MS4A6A AI184968 C1QG NM023003.1 TM6SF1 AL161725 FLJ00026 NM016184.1 CLECSF6 NM018440.1 PAG NM031284.1 DKFZP434B195 AL553942 FLJ31951 BC002342.1 CORO1C AI394438 N/A AA775177 PTPRE T64884 N/A AL162070.1 CORO1C T64884 N/A AF253977.1 MS4A6A AW511319 N/A AF237908.1 MS4A6A AI640834 RA-GEF-2 W03103 DDEF1 AI655467 N/A AK022888.1 FENS-1 AL161725 FLJ00026 AI141784 N/A T92908 N/A

TABLE 6 Genes With Down-Regulated Expression In Both stage I And stage II Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM004092.2 ECHS1 BC002449.1 FLJ13612 NM000270.1 NP J02639.1 SERPINA5 NM002354.1 TACSTD1 BC002571.1 DKFZP564O243 AF017987.1 SFRP1 U03884.1 KCNJ1 NM003012.2 SFRP1 AF173154.1 HYAL1 NM000666.1 ACY1 AF130103.1 PBP NM000191.1 HMGCL AL117618.1 PDHB NM015254.1 KIF13B AF063606.1 N/A NM000140.1 FECH BC005314.1 N/A U75667.1 ARG2 BF686267 PBP NM000196.1 HSD11B2 AI742553 PRKWNK1 NM014636.1 RALGPS1A D83782.1 SCAP NM001441.1 FAAH AB029031.1 TBC1D1 NM005978.2 S100A2 AK025432.1 KIAA0564 NM001678.1 ATP1B2 AL117643.1 N/A NM001099.2 ACPP AW772192 N/A NM014731.1 ProSAPiP1 NM003944.1 SELENBP1 BF343007 N/A AL049977.1 CLDN8 NM000035.1 ALDOB AK023937.1 THEA NM005950.1 MT1G AK025084.1 TNRC9 NM002371.2 MAL X03363.1 ERBB2 NM006984.1 CLDN10 AK026411.1 ALDOB NM002567.1 PBP NM016026.1 RDH11 NM000019.1 ACAT1 NM016286.1 DCXR NM001692.1 ATP6V1B1 NM019027.1 FLJ20273 X77737.1 N/A BG338251 RAB7L1 NM006226.1 PLCL1 NM006113.2 VAV3 NM000893.1 KNG NM018075.1 FLJ10375 NM000412.2 HRG NM013271.1 PCSK1N NM001963.2 EGF NM017586.1 C9orf7 NM003361.1 UMOD NM016321.1 RHCG NM000050.1 ASS NM025247.1 MGC5601 NM001438.1 ESRRG BC002449.1 FLJ13612 NM020632.1 ATP6V0A4 AI379517 N/A AI632015 SLC12A1 AA058832 MGC33926 NM000701.1 ATP1A1 AW274034 N/A NM031305.1 DKFZP564B1162 AI580268 NUDT6 AF130089.1 ALDH6A1 AI761947 DKFZP564B1162 AK025651.1 N/A AI793201 N/A W45551 MMP24 AK025898.1 N/A W67995 FXC1 AB046810.1 C20orf23 AL136566.1 IBA2 AK024204.1 N/A AF105366.1 SLC12A6 BF594722 N/A AF284225.1 DMRT2 R88990 N/A AA191708 N/A N73742 N/A AL355708.1 N/A AI697028 FLJ90165 BE783949 FLJ10101 BF590528 N/A AL529672 N/A AI733359 N/A AL568674 MYBBP1A H20179 N/A AU147564 CLMN AA991551 MGC14839 AK000208.1 N/A AI758950 SLC26A7 AB051536.1 FLJ14957 AA911561 N/A AI569747 TFDP2 AI769774 N/A AK025562.1 N/A AA669135 N/A AI660243 TMPRSS2 AW136060 SLC13A2 N50413 N/A AI733593 N/A AI347918 N/A BF739841 N/A AL536553 GRP58 AA600175 N/A BC000282.1 LOC89894 BF477980 N/A BF106962 FAM3B AI934557 N/A AI051248 FLJ32115 BE326951 KNG AI928242 N/A AI632567 N/A BG236006 N/A BE300882 N/A AI653107 N/A BE855713 N/A AI824037 FLJ25461 AA485440 DBP R61322 N/A AA915989 FLJ10743 AW071744 KCNJ10 AA085764 SIGIRR BF059276 N/A

EXAMPLE 6 Loss of TGF-β Receptor Expression Demonstrated By Gene Array And Real-Time PCR In Renal Cell Carcinoma

Expression of type I TGF-β receptor (TBR1), type II TGF-β receptor (TBR2), and type III TGF-β receptor (TBR3) mRNA were compared in normal renal tissue, primary renal cell carcinoma without metastasis, primary lesions of metastatic renal cell carcinoma, and metastatic lesions. A summary of gene array analysis was presented as average signal intensities in FIG. 11A (mean±standard error). The signal intensity for TBR1 (cross-hatched bars) was relatively low, although TBR1 was scored as ‘Present’ in all samples. No significant changes in TBR1 expression were observed. TBR2 (gray bars) was abundantly expressed in normal epithelium and in primary lesions of nonmetastatic renal cell carcinoma. TBR2 was significantly reduced in primary lesions with metastatic disease (P<0.028 by ANOVA). TBR2 was even more reduced in metastatic lesions. TBR3 expression was high in normal epithelium, but was significantly reduced in each of the five primary tumors with nonmetastatic disease (black bars). TBR3 expression was also reduced in primary tumors with metastatic lesions and in metastatic lesions themselves.

These expression patterns were confirmed by real-time PCR (Tagman®) in the 10 patients used for gene array analysis. Means and standard errors for individual samples are shown in FIG. 11B. All data were normalized to 18S rRNA and calibrated to target abundance in the paired normal tissues. TBR1 mRNA abundance did not change (cross-hatched bars), consistent with the gene chip data. TBR2 (gray bars) was not reduced in primary tumors without metastases, whereas TBR2 was significantly reduced in primary tumors with metastatic disease and in metastatic lesions. TBR3 was reduced in all tumors (black bars).

The investigators have subsequently completed real-time PCR analysis of TBR1, TBR2, and TBR3 expression in 16 primary tumors without metastases (plus paired normal epithelium) and nine samples of primary tumors with metastatic disease, paired metastatic lesions, and paired normal tissue. The data were consistent with those shown for the samples analyzed in FIG. 11A. TBR3 expression was significantly reduced in all tumors; whereas TBR2 expression was reduced in only 1/16 primary tumors without metastatic lesions, but was reduced in primary tumors with metastatic lesions (8/9). These data show that loss of TBR3 is an early event in renal cell carcinoma, strongly suggesting that TBR3 plays a critical role in renal cell carcinoma carcinogenesis.

The loss of TBR3 mRNA expression was also correlated with TNM scores (T, histological score; N, lymph node number; M, number of organ metastases) from patient samples (data not shown). TBR3 mRNA expression was suppressed in the earliest stage, stage I, and was found to be suppressed in all tumor stages (I-IV). In addition, loss of TBR2 in the primary tumor is significantly associated with acquisition of the metastatic phenotype and clinically manifests as metastatic progression.

EXAMPLE 7 Attenuation of TGF-β-Mediated Signal Transduction In Human Renal Cell Carcinoma

Decreased type III TGF-β receptor (TBR3) mRNA expression in all tumors was associated with failure to detect TBR3 protein by immunohistochemistry (FIG. 12). Type I TGF-β receptor (TBR2) protein was detected in localized tumor (primary, no mets), but was not detectable in primary tumors with metastatic disease or in corresponding metastatic lesions. Type I TGF-β receptor (TBR1) protein was detected in normal tissue and in all tumor samples.

The investigators hypothesized that these losses seen in TGF-β receptor expression would manifest as an attenuation of TGF-β mediated signal transduction, and would significantly alter the expression of TGF-β regulated genes. From the gene array data disclosed above, 13 known TGF-β/Smad-regulated genes were down-regulated in renal cell carcinoma (Table 7). Using mRNA from 35 patient-matched samples, the investigators verified loss of expression of three of these genes by comparing matched normal and tumor tissue. Real-time PCR was used to measure the expression of Collagen IV type 6, fibulin-5, and connective-tissue growth factor (CTGF). Collagen IV type 6 (gray bars) is an extracellular matrix protein that plays a critical role in the regulation of membrane integrity and cell signaling. Fibulin-5 is a recently discovered TGF-β-regulated gene, which has tumor suppressor activity. Fibulin-5 is an extracellular matrix protein that is believed to signal through interaction with integrins. CTGF is a secreted protein involved in angiogenesis, skeletogenesis, and wound healing. CTGF enhances TGF-β1 binding to TBR2, and CTGF and TGF-β collaborate to regulate the expression of extracellular matrix proteins during renal fibrosis. As summarized graphically in FIG. 13, all the evaluated TGF-β-regulated genes were down-regulated in early tumor stages, suggesting that renal cell carcinoma undergoes loss of TGF-β responsiveness at an early stage. These data indicate that this loss of TGF-β sensitivity is due, primarily, to loss of type III TGF-β receptor (TBR3) in early tumor development and further loss of sensitivity in metastatic disease is mediated through subsequent loss of type II TGF-β receptor (TBR2).

TABLE 7 Known TGF-β-Regulated Genes Found To Be Down-Regulated In Localized Tumors By Gene Array Analysis Fold GenBank No. Gene Name Attenuation S81439 TGFβ-induced early growth factor (TIEG) 2.5 AF093118 Fibulin 5 4.0 U42408 Ladinin 1 15.4 U01244 Fibulin 1 4.8 J05257 Dipeptidase 1 7.7 D21337 Collagen, type IV, a6 3.6 X80031 Collagen, type IV, a3 2.4 M64108 Collagen, type XIV, a1 3.2 M98399 Collagen, type I receptor 4.2 L23808 Matrix metallo-proteinase 12 3.7 M35999 Integrin, b3 2.5 AI304854 p27^(Kip1) 2.1 J05581 Mucin 1 6.5 Data were analysed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0, and hierarchical cluster analysis using Spotfire to identify genes that are down-regulated in local tumors versus that of normal renal cortex tissue.

EXAMPLE 8 TGF-β Receptor Expression In Renal Cell Carcinoma Cell Lines

Human renal cell carcinoma cell lines were identified that recapitulate the clinical observations of TGF-β receptor biology described above. UMRC6 cells were derived from a clinically localized human renal cell carcinoma (Grossman et al., 1985). As shown in FIG. 14A, UMRC6 cells express type II TGF-β receptor (TBR2) mRNA, but not type III TGF-β receptor (TBR3). Immunohistochemical analysis (FIG. 14B) confirms the presence of TBR2 protein and the absence of TBR3 expression. UMRC3 cells were derived from the primary tumor of a patient with metastatic renal cell carcinoma. This highly aggressive cell line lacks detectable TBR2 and TBR3 mRNA (FIG. 14A) and protein (FIG. 14B).

In addition to these relevant laboratory models, normal renal epithelial (NRE) tissue was harvested from nephrectomy specimens and established as primary cultures (Trifillis, 1999). As shown in FIGS. 14A and 14B, these primary cultures of NRE expressed TBR3, TBR2, and TBR1 mRNA and protein in vitro. NRE cells can be grown in culture for 10 passages and were easily isolated and characterized. NRE cells were characterized for cytokeratin expression and tubule-specific gene expression, for example, megalin (data not shown). Thus, there are relevant cell models in which TBR2 and TBR3 expression can be manipulated to examine the impact of TGF-β receptor biology on the carcinogenesis and progression of human renal cell carcinoma in vitro.

EXAMPLE 9 TGF-β Activity In Renal Cell Carcinoma Cell Lines

It is well known that TGF-β1 inhibits cell proliferation in epithelial cells. The present example demonstrates the effects of TGF-β on renal tumor cell proliferation.

DNA content of cells was used as a measure of cell proliferation. Cells were plated at 20,000 cells/well in 12-well plates. Cells were grown in 10% FBS:DMEM:penicillin:streptomycin. The following day, media were exchanged with appropriate treatment added to the media. On day 3 of treatment, cells were analyzed for DNA content using Hoechst reagent. DNA standard was used to correlate DNA content per well.

As shown in FIG. 15A (squares), TGF-β1 inhibited the proliferation of normal renal epithelial cells in culture. URMC3 cells expressed neither type II or type III TGF-β receptors and, not surprisingly, were resistant to the inhibitory effects of TGF-β on cell proliferation (triangles, FIG. 15A). UMRC6 cells expressed type II but not type III TGF-β receptors, and were partially resistant to TGF-β1 (circles, FIG. 15A).

TGF-β transcriptional activity was also measured in the above cell models using transient transfection of the 3TP/lux reporter, which contains an AP-1/Smad3 response element from the PAI-1 promoter. This luciferase reporter construct demonstrates increased transcriptional activity in response to exogenous TGF-β-mediated signal transduction. 3TP/lux was transiently transfected along with SV/renilla luciferase (Promega) into cells using fugene (Roche) as the transfection agent. Cells were treated with or without TGF-β1 24 h after transfection and luciferase activity (Promega Luciferase Assay system and Lumat luminometer) was determined 24 h after TGF-β treatment. Firefly luciferase activity was normalized using the ratio of firefly luciferase/renilla luciferase. As shown in FIG. 15B, normal renal epithelial cells were highly responsive to 2 ng/ml (80 pM) of TGF-β1. UMRC6 cells demonstrated significantly less luciferase activity in response to TGF-β1, and UMRC3 cells were entirely unresponsive.

EXAMPLE 10 Recapitulation of TGF-β Signaling Through Reintroduction of TGF-b Receptor Expression Into Renal Cell Carcinoma

To test whether reintroduction of TGF-β receptor expression would result in re-establishment of TGF-β signal transduction and reacquisition of TGF-β cellular sensitivity, UMRC3 cells were engineered to express stably either type II TGF-β receptor (+TBR2) alone or type II plus type III TGF-β receptor (+TBR2+TBR3).

Plasmid construction and transfection were described as follows. The complete coding sequences for human type II TGF-β receptor (TBR2) was cloned into the EcoRI/XbaI site of pcDNA3/FLAG. The expression vector was stably transfected into UMRC3 cells using fugene as DNA carrier and genticin as selection antibiotic (Sigma, 1 mg/ml). Ten clones (UMRC3/TBR2) were selected and verified for TBR 2 mRNA and protein expression such as Western analysis using the FLAG antibody (data not shown). From these cell clones, one was to be selected that had equivalent protein expression of TBR2 to that of normal renal epithelial (NRE) and UMRC6 cells.

The type III TGF-β receptor (TBR3) coding sequence was PCR amplified from a plasmid expressing wild-type TBR3 in pSV7d (a gift from Dr C-H Heldin). TBR3 was then cloned into the EcoRI site of pcDNA4/TO/myc-His® (InVitrogen) in the sense and antisense (negative control) orientation. The orientation and sequence of TBR3 was verified. The antisense TBR3 (As TBR3) vector was used as a control. TBR3/pcDNA4/TO/myc-His and As TBR3/pcDNA4/TO/myc-His vectors were stably transfected into UMRC3/TBR2 cells. A clone was selected that demonstrated an equivalent expression of TBR3 mRNA to that of normal renal epithelial cells. As a control for UMRC3+TBR2 and UMRC3+TBR2+TBR3, wild-type UMRC3 were stably transfected with both pcDNA/FLAG and pcDNA4/TO/myc-His vectors.

As shown in FIGS. 16A-16B, stable transfection of type II TGF-β receptor (TBR2) alone or type II plus type III TGF-β receptor (TBR2+TBR3) resulted in detectable levels of mRNA for each receptor on RT-PCR analysis. On examining the in vitro growth kinetics of these re-engineered cells, it was noted that reintroduction of TBR2 resulted in a twofold reduction in cell proliferation and reintroduction of both TBR2 and TBR3 resulted in a fourfold reduction in cell proliferation with the addition of exogenous TGF-β.

The investigators then examined TGF-β-mediated transcriptional activity as a consequence of TGF-β receptor re-expression. As shown in FIG. 16C, reintroduction of TBR2 partially restored transcriptional responsiveness, as evidenced by a 5.6-fold increase in 3TP/lux activity after addition of TGF-β1. Reintroduction of both TBR2 and TBR3 into UMRC3 cells resulted in 17.5-fold increase in 3TP/lux activity after addition of TGF-β1.

To demonstrate reestablishment of TGF-β-regulated gene expression, collagen IV type 6 mRNA expression was examined by real-time PCR in these re-engineered cell lines in the presence of TGF-β1. As shown in FIG. 16D, reexpression of TBR2 in UMRC3 cells results in a sevenfold increase in collagen IV type 6 mRNA levels over that of UMRC3 controls, while reintroduction of both TBR2 and TBR3 enhanced collagen IV type 6 mRNA expression 11-fold. These data are consistent with a number of published reports that indicate expression of TBR3 is essential for full TGF-β responsiveness.

UMRC3 cells have been shown to be tumorigenic in athymic nude mice (Grossman et al., 1985). Anchorage independent growth in soft agar is a well-established in vitro correlate of in vivo tumorigenicity. Colonies formation in soft agar was determined as follows. UMRC3 (pcDNA/FLAG and pcDNA4/T0/myc-His empty vectors), UMRC3+TBR2, or UMRC3+TBR2+TBR3 cells were plated at 1000 cells/60 mm dish in an agarose/FBS/media sandwich in the presence of 2 ng/ml TGF-β. No selection antibodies were added to the agarose media mixture. The cells were incubated for 45 days to insure that no colony formation would occur. Cells were then stained with 0.005% Crystal Violet, photographed, and assessed for number and size of colonies.

As shown in FIG. 16E, UMRC3 cells demonstrated anchorage independent growth in soft agar. Reintroduction of TBR2 into UMRC3 cells significantly decreased the number and size of colonies that formed in soft agar. Reintroduction of both TBR2 and TBR3 completely abrogated the ability of UMRC3 cells to form colonies in soft agar, even after 45 days in culture. These data demonstrate that reintroduction of TBR2 resensitizes UMRC3 cells to the effects of exogenous TGF-β through reacquisition of TGF-β signal transduction. More interestingly, however, reintroduction of TBR3 in the presence of TBR2 into UMRC3 cells significantly enhanced TGF-β-regulated gene transcription, growth inhibition, and loss of anchorage-independent growth over that seen with reintroduction of TBR2 alone. These data clearly show that renal cell carcinoma cells are TGF-β resistant. Loss of TBR3 expression occurs early and appears to be associated with a relatively less aggressive state that is partially TGF-β responsive. Loss of TBR2 results in frank TGF-β resistance and is associated with acquisition of a more aggressive phenotype.

FIGS. 17-18 demonstrate that re-expression of type II or type Ill TGF-β receptor in the highly metastatic human renal cell carcinoma cell line UMRC3 inhibited cell proliferation in cell culture and tumor growth in a nude mouse model. The TGF-β receptors were either re-expressed in a stable vector system or as an adenoviral vector. For clinical purposes, it would be envisioned to treat patients with an adenovirus expressing one or both of the TGF-β receptors to block tumor growth or cause tumor regression.

EXAMPLE 11 Stepwise Sequential Loss of Type Ill and Type II TGF-β Receptor Expression in Renal Cell Carcinoma

With genomic profiling in human renal cell carcinoma, the data presented above demonstrated a stepwise sequential loss of type III and type II TGF-β receptor expression in association with renal cell carcinogenesis and progression. These findings were confirmed by both immunohistochemistry and real-time PCR in patient-matched tissue samples. This clinical observation was brought to the laboratory to identify relevant in vitro models. Using these models, it was demonstrated that loss of type III TGF-β receptor expression resulted in incremental desensitization to TGF-β and attenuation of TGF-β signaling. Subsequent loss of type II TGF-β receptor resulted in complete loss of TGF-β sensitivity. With in vitro modulation of TGF-β receptor expression, it was demonstrated that reconstitution of the TGF-β signaling pathway resulted in significant growth inhibition and loss of the aggressive phenotype.

These experiments are unique in that clinically relevant observations, which are derived from the evaluation of gene expression in normal renal cortical tissue, localized renal cell carcinoma and metastatic renal cell carcinoma, were brought to the laboratory for validation and experimental manipulation in relevant in vitro models. Other investigators have examined human renal cell carcinoma cell lines and identified alterations in the expression of TGF-β signaling pathway intermediaries, but those observations have not been validated in the clinical biology of renal cell carcinoma. To the investigators' knowledge, few studies have methodically examined the expression of all three TGF-βreceptors in patient samples at the protein and mRNA level in an effort to correlate TGF-β receptor expression to disease-specific states of renal cell carcinoma (i.e. localized versus metastatic tumor). A major strength of the present study is that the investigators recognized distinct disease states in renal cell carcinoma, associated them with specific alterations in the TGF-β signaling pathway, and then validated and manipulated the clinical observations in the laboratory.

Although the mechanisms are not well understood, it is clear that TGF-β regulates a large number of diverse biological functions, including cell proliferation, differentiation, cell adhesion, apoptosis, extracellular matrix production, immune regulation, neuroprotection, and early embryonic development. In epithelial cells, the effect of TGF-β is generally to inhibit proliferation, promote cellular differentiation, and regulate interactions with the extracellular matrix. As a direct consequence, aberrations in TGF-β signaling can have a dramatic impact on cellular processes that are critically associated with neoplastic and malignant transformation. Given the well-documented observation that the end result of TGF-β signaling is largely growth inhibitory, it makes intuitive sense that cancer cell would develop mechanisms to escape TGF-β sensitivity. To date, these mechanisms have not been elucidated in human renal cell carcinoma.

Based on the data presented above, the investigators hypothesize that this escape from the growth-inhibitory effects of TGF-β is mediated through the stepwise sequential loss of type III and type II TGF-β receptor expression. To the investigators' knowledge, no one has linked sequential loss of these two types of receptors to carcinogenesis and metastatic progression in oncology. This is the first time that stepwise loss of a single transduction pathway has been associated with important biologic sequelae in a human cancer.

Results presented in the present invention demonstrate that loss of type III TGF-β receptor expression is an early event in renal cell carcinoma biology and that this loss has important sequelae with regard to renal cell carcinoma carcinogenesis and progression. All clinical samples of localized renal cell carcinoma demonstrated loss of type III TGF-β receptor, but had normal expression of type I and type II TGF-β receptors. Replication of this clinical observation in in vitro models demonstrated significant loss of TGF-β sensitivity, manifest as a significant reduction in the growth inhibitory effects of TGF-β1 and significantly reduced TGF-β-mediated transcription. Interestingly, cell lines derived from localized RCC retained type II TGF-β receptor expression and therefore, still demonstrated sensitivity, albeit reduced, to TGF-β. Only with metastatic progression and loss of type II TGF-β receptor expression does the cell become completely resistant to the effects of TGF-β. The investigators hypothesize that this retained, but attenuated, TGF-β signaling seen in local tumors must convey some as yet unrecognized biologic benefit for local tumors that is no longer required, and therefore discarded, with metastatic progression. In fact, this loss of type II TGF-β receptor expression may be an absolute integral component in the cascade of intracellular events that lead to the development of metastatic potential. In keeping with this hypothesis, it has been shown that loss of type I TGF-b receptor expression was one of 40 integral alterations of gene expression to predict for poor prognosis of patients diagnosed with renal cell carcinoma.

In summary, the above results demonstrate a clear link between loss of type III TGF-β receptor expression to a human disease state. Reduced type III TGF-β receptor (TBR3) expression has been reported in human breast tumor cell lines, suggesting that loss of TBR3 expression may be a more ubiquitous phenomena in carcinogenesis, rather than an isolated finding in human RCC biology. The fact that the investigators found down-regulation of TBR3 in every renal cell carcinoma specimen studied to date (35 patients) and that re-expression of TBR3 (in the presence of re-expressed TBR2) completely abolish growth on soft agar suggests an important role for TBR3 in normal renal epithelial homeostasis that must be abrogated for renal cell carcinogenesis and progression to occur. Little attention has been given to TBR3 in normal cell biology or the changes in expression that occur with carcinogenesis and progression. Observations from the present invention would suggest that TBR3 plays an important functional role in signaling and that loss of expression is an important event in the acquisition of the tumorigenic and metastatic phenotype

EXAMPLE 12 Genomic Profiling For stage I Papillary Renal Cell Carcinoma And Benign Oncocytoma

FIG. 19 shows hierarchical clustering of genes over-expressed or down-regulated (with at least 2 fold differences) in stage I papillary renal cell carcinoma verses normal renal cortex. Genes over-expressed and down-regulated in stage I papillary renal cell carcinoma are listed in Table 8 and Table 9 respectively. FIG. 20 shows hierarchical clustering of genes over-expressed or down-regulated (with at least 2 fold differences) in benign oncocytoma verses normal renal cortex. Genes over-expressed and down-regulated in benign oncocytoma are listed in Table 10 and Table 11 respectively. FIG. 21 shows venn analysis of gene distribution among stage I renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma. Genes with at least 2-fold differences in expression were filtered at 95% confidence level (CL) in the following 3 t-tests: stage I RCC vs. normal; oncocytoma vs. normal; and stage I papillary renal cell carcinoma vs. normal. Six hundred twenty five genes were present only in stage I RCC (95% CL), 136 genes were present only in oncocytoma (95% CL), 344 genes were present only in stage I papillary renal cell carcinoma (95% CL), and 60 genes were common to stage I RCC, oncocytoma and stage I papillary renal cell carcinoma. FIG. 22 shows venn analysis of gene distribution among stage II renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma. Genes with at least 2-fold differences in expression were filtered at 95% confidence level (CL) in the following 3 t-tests: stage II RCC vs. normal; oncocytoma vs. normal; and stage I papillary renal cell carcinoma vs. normal. One thousand and five genes were present only in stage II RCC (95% CL), 152 genes were present only in oncocytoma (95% CL), 334 genes were present only in stage I papillary renal cell carcinoma (95% CL), and 43 genes were common to stage II RCC, oncocytoma and stage I papillary renal cell carcinoma.

TABLE 8 Genes With Up-Regulated Expression In stage I Papillary Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM_003505 FZD1 AC004382 DKFZP434K046 AL035683 B4GALT5 NM_000248 MITF R56118 N/A NM_022154 SLC39A8 NM_014575 SCHIP1 AI436813 N/A AI694320 ZNF533 AF007162 CRYAB BC031322 N/A NM_015392 NPDC1 BF346665 N/A AL136585 DKFZp761A132 BC004283 LOC283639 AB040120 SLC39A8 AF302786 GNPTAG NM_138473 SP1 AU121975 PAICS AU144387 182-FIP NM_016315 GULP1 NM_022763 FAD104 AL541302 SERPINE2 AI093231 APBB1IP BG391217 C9orf80 NM_000235 LIPA NM_000700 ANXA1 AI817079 EXOC7 N30188 N/A NM_004385 CSPG2 NM_003651 CSDA NM_024801 TARSH AI830227 FLII BF218922 CSPG2 U20350 CX3CR1 BF590263 CSPG2 NM_005692 ABCF2 NM_001233 CAV2 U34074 AKAP1 AB020690 PNMA2 AB056106 TARSH AW188198 TNFAIP6 AU151483 CDH6 NM_007115 TNFAIP6 BC026260 TTC3 AI742838 DOCK11 AL133001 SULF2 AW117264 N/A NM_003358 UGCG AF016266 TNFRSF10B NM_001282 AP2B1 NM_013952 PAX8 AF322067 RAB34 AA771779 ZFP90 NM_001540 HSPB1 W72333 FLJ21657 N58363 STATIP1 H23979 MOX2 AF072872 FZD1 BG542521 PPM2C BF247552 SLC38A1 AF063591 MOX2 X69397 CD24 BF247383 BMPR2 BC000251 GSK3B NM_005114 HS3ST1 BF691447 B4GALT5 BE466145 N/A AB046817 SYTL2 BC005352 TNFAIP8 AF255647 DKFZP566N034 AC002045 LOC339047 BF344237 N/A BC040558 D2LIC AW242720 LOC143381 U13699 CASP1 AA115485 MGC3222 NM_002718 PPP2R3A NM_006588 SULT1C2 BF476502 MPPE1 NM_000546 TP53 BC034275 LOC253982 N92494 JWA AF279145 ANTXR1 W74580 MGC3222 AV724216 NDRG4 AF131749 PSK-1 BG165613 N/A AW026491 CCND2 NM_018205 LRRC20 NM_012410 PSK-1 NM_022083 C1orf24 NM_002800 PSMB9 NM_006169 NNMT BF512748 JAK3 AF141347 TUBA3 AA404269 PRICKLE1 NM_000064 C3 M33376 AKR1C1 AV710838 BCDO2 AF035321 DNM1 AI417917 EHD2 NM_002862 PYGB AI681260 LILRB1 AF132000 DKFZP564K1964 NM_000389 CDKN1A L07950 HLA-C AF288391 C1orf24 AF114011 TNFSF13 NM_002627 PFKP BF674052 VMP1 NM_001975 ENO2 AI922599 VIM NM_030786 SYNCOILIN AF044773 BANF1 NM_006169 NNMT NM_015925 LISCH7 AI417917 EHD2 NM_001684 ATP2B4 NM_006868 RAB31 AI123348 CHST11 L03203 PMP22 NM_001304 CPD AF199015 VIL2 NM_006762 LAPTM5 AI873273 SLC16A6 NM_000211 ITGB2 NM_017821 RHBDL2 AA995910 ALOX5 BF740152 MYO1F NM_018965 TREM2 AA954994 N/A AL353715 STMN3 AI458735 MGC26717 BC019612 C20orf75 NM_003254 TIMP1 AF086074 N/A AI688631 N/A NM_005045 RELN AK026037 N/A AI935123 C14orf78 BG327863 CD24 AL550875 C7orf28B NM_016008 D2LIC L27624 TFPI2 AI394438 LOC253981 AL574096 TFPI2 AA947051 D2LIC AA005141 MET AI819043 N/A D86983 D2S448 AI378044 UGCG AW439242 C6orf68 NM_024576 OGFRL1 AB000221 CCL18 M76477 GM2A NM_002121 HLA-DPB1 NM_002214 ITGB8 U17496 PSMB8 AI879381 ADCK2 U05598 AKR1C1 NM_000152 GAA BF342851 D2S448 H15129 MEIS4 BF311866 PTGFRN L42024 HLA-C NM_001449 FHL1 NM_002178 IGFBP6 AA954994 N/A AI761561 HK2 Y13710 CCL18 AA722799 DCBLD2 BG170541 MET NM_003255 TIMP2 AB037813 DKFZp762K222 NM_000107 DDB2 D28124 NBL1 AV699565 CTSC NM_021103 TMSB10 NM_000861 HRH1 AI949772 N/A

TABLE 9 Genes With Down-Regulated Expression In stage I Papillary Renal Cell Carcinoma Genbank ID Gene Symbol AF232217 N/A NM_003877 SOCS2 AI823572 MGC45438 AI768894 CGN AU154994 SLC13A3 AW772192 N/A AW979271 N/A AF094518 ESRRG AF064103 CDC14A T40942 ANGPTL3 AI524125 PCDH9 NM_001146 ANGPT1 AI733474 GPR155 AI242023 N/A AI767756 HS6ST2 BF970431 N/A NM_000412 HRG NM_005670 EPM2A NM_021614 KCNN2 AW071744 KCNJ10 M13149 HRG AI928242 TFCP2L1 H17038 N/A AI769774 LOC155006 NM_002010 FGF9 AW274034 USP2 AI635774 EMCN NM_004633 IL1R2 AW007532 IGFBP5 NM_003289 TPM2 NM_004070 CLCNKA BF512388 C10orf58 NM_014621 HOXD4 BC005830 ANXA9 AI733593 N/A NM_000362 TIMP3 NM_020632 ATP6V0A4 NM_001438 ESRRG AI697028 FLJ90165 AU146204 ENPP6 AA897516 PTGER4 AA775681 FLJ23091 NM_024307 MGC4171 AI393205 ACY-3 J02639 SERPINA5 AF017987 SFRP1 NM_000085 CLCNKB NM_005951 MT1H AA058832 MGC33926 NM_005950 MT1G BF059276 N/A NM_021805 SIGIRR BC043647 LOC284578 AA557324 CYP4X1 AL161958 THY1 BF528646 DKFZP564I1171 AL121845 KIAA1847 AW340112 LOC401022 AY079172 ATP6V0D2 R73554 IGFBP5 AA928708 CYP8B1 AI826437 N/A H71135 ADH6 AV720650 KIAA0888 NM_000102 CYP17A1 AA780067 HS3ST3B1 Z92546 SUSD2 NM_000640 IL13RA2 AL558479 THY1 AI806338 TBX3 BC005314 ALDOB NM_003155 STC1 NM_173591 FLJ90579 AA931562 N/A BF510426 N/A AI694325 N/A AF331844 SOST AF205940 EMCN X77737 SLC4A1 NM_001290 LDB2 NM_004392 DACH1 NM_016242 EMCN BC001077 LOC87769 AW014927 CALB1 AA218868 THY1 AI758950 SLC26A7 BF478120 RECQL5 AK024256 KIAA1573 BC041158 CYP4A11 BF726212 ANK2 AI623321 MTP AI985987 SCNN1G AI796189 PAH AW242408 UPP2 NM_021161 KCNK10 NM_000860 HPGD NM_000163 GHR BF447963 KIAA0962 AL136880 ESPN BF941499 GPR116 NM_024426 WT1 AW242409 N/A M61900 PTGDS BF509031 ATP6V1G3 AW963951 SIAT7C NM_000934 SERPINF2 AW340588 MAN1C1 BF248364 AF15Q14 AI263078 SLC23A3 AL534095 FLJ23091 BF130943 PPAPDC1 NM_004929 CALB1 AI732596 N/A AI222435 N/A AA603467 ZNF503 NM_005397 PODXL R41565 N/A AI090268 N/A AI951185 NR2F1 AI300520 STC1 NM_002609 PDGFRB BC006236 MGC11324 NM_006984 CLDN10 NM_024609 NES BG413612 N/A NM_002591 PCK1 D64137 CDKN1C NM_005410 SEPP1 AK026344 PEPP2 AB020630 PPP1R16B AI670852 PTPRB AF022375 VEGF AI693153 GABRB3 NM_016246 DHRS10 NM_001393 ECM2 AA873542 SLC6A19 N93191 PR1 U95090 PRODH2 BC005090 AGMAT D26054 FBP1 NM_000717 CA4 AI732994 MGC13034 D38300 PTGER3 NM_000151 G6PC AI650260 N/A AK025651 PNAS-4 BC024226 IFRG15 AF161441 N/A BC006294 DHRS10 AF161454 APOM NM_003039 SLC2A5 NM_022129 MAWBP AI675836 SORCS1 AI733515 MGC52019 NM_005276 GPD1 NM_001443 FABP1 NM_014298 QPRT AI433463 MME M10943 MT2A AL049313 N/A NM_005952 MT1X BF195998 ALDOB NM_002450 MT1X NM_022829 SLC13A3 NM_002910 RENBP NM_000035 ALDOB BF246115 MT1F NM_007287 MME AF078844 MT1F NM_003399 XPNPEP2 AF170911 SLC23A1 NM_000196 HSD11B2 AF333388 MT1H BF431313 N/A NM_003500 ACOX2 NM_004844 SH3BP5 AA995925 N/A NM_003206 TCF21 NM_001218 CA12 AI311917 DPYS BF432333 FLJ31196 AA843963 PRLR NM_001385 DPYS NM_017753 PRG-3 NM_003052 SLC34A1 NM_006633 IQGAP2 NM_000778 CYP4A11 NM_001133 AFM AL136551 SESN2 T90064 N/A NM_000792 DIO1 BF696216 N/A NM_016725 FOLR1 NM_004413 DPEP1 NM_019101 APOM Z98443 FLJ38736 NM_014270 SLC7A9 NM_018456 EAF2 AF124373 SLC22A6 AW771563 N/A NM_016327 UPB1 NM_014495 ANGPTL3 NM_024734 CLMN AI074145 KMO NM_016527 HAO2 NM_000896 CYP4F3 NM_003645 SLC27A2 NM_001072 UGT1A6 AB051536 FLJ14957 AI631993 N/A NM_025149 FLJ20920 NM_000277 PAH BC005939 PTGDS M74220 PLG AL574184 HPGD AI935789 UMOD NM_000161 GCH1 NM_002472 MYH8 H57166 N/A BC020873 CLCNKA NM_000597 IGFBP2 NM_000550 TYRP1 NM_000790 DDC AA806965 BTNL9 NM_004668 MGAM NM_020163 LOC56920 NM_021027 UGT1A6 NM_004490 GRB14 AF348078 GPR91 AA788946 COL12A1 NM_016347 NAT8 AW242315 N/A AF338650 PDZK3 AI735586 LOC152573 BE221817 CNTN3 R88990 N/A NM_004476 FOLH1 NM_003278 TNA NM_004615 TM4SF2 NM_007180 TREH NM_023940 RASL11B AW173045 TBX2 AI742872 SLC2A12 U28049 TBX2 BC001196 HS6ST1 NM_001395 DUSP9 AW195353 TFCP2L1 NM_000336 SCNN1B NM_003122 SPINK1 U43604 N/A NM_144707 PROM2 BC029135 N/A AI653981 L1CAM NM_005414 SKIL AI796169 GATA3 BQ894022 PDE1A M96789 GJA4 NM_013335 GMPPA N74607 AQP3 NM_003221 TFAP2B NM_014059 RGC32 BF057634 HOXD8 AI572079 SNAI2 AA523172 N/A AI056877 N/A AF319520 ARG99 NM_006206 PDGFRA NM_002885 RAP1GA1 AW771314 MGC35434 NM_003361 UMOD NM_016955 SLA/LP NM_000142 FGFR3 AI569804 LOC375295 NM_000893 KNG1 NM_001584 C11orf8 BC029135 N/A BG261252 EVI1 NM_147174 HS6ST2 NM_006226 PLCL1 NM_000218 KCNQ1 NM_001172 ARG2 U03884 KCNJ1 AL050264 TU3A X83858 PTGER3 BC003070 GATA3 BF439270 N/A AL120332 MGC20785 AA911235 MST1 NM_000459 TEK NM_000955 PTGER1 AW242836 LOC120224 NM_022844 MYH11 AI926697 Gup1 BC042069 N/A NM_000486 AQP2 NM_005518 HMGCS2 AI870306 IRX1 NM_001963 EGF AW264204 CLDN11 AI632015 SLC12A1 BF431989 THRB AF339805 N/A AI459140 N/A BF106962 FAM3B NM_001864 COX7A1 NM_005019 PDE1A AI471866 SLC7A13 AU146305 PDE1A AI653107 NRK NM_000663 ABAT NM_004466 GPC5 AU119437 LOC144997 BF195936 KRT18L1 BC036095 DRP2 NM_022454 SOX17 R49295 N/A AW299531 HOXD10 AI623202 PRDM16 AL137716 AQP6 AW452355 N/A AI332407 SFRP1 AA563621 HSPB6 AL565812 PTN X15217 SKIL AI452457 LOC199920 AK095719 N/A AI281593 DCN AI056187 N/A M21692 ADH1B AI668598 N/A AI660243 TMPRSS2 AI700882 SLC13A3 AI754423 FLJ38507 NM_000963 PTGS2 AA759244 FXYD4 AW051712 N/A U75667 ARG2 AL832099 MGC33190 NM_000930 PLAT AK057337 LOC145820 AF083105 SOX13 AW300204 SLC30A8 NM_013231 FLRT2 NM_005856 RAMP3 BI825302 PR1 AI458003 CYYR1 NM_003012 SFRP1 AK026877 N/A AF138300 DCN AI632567 N/A AU155612 N/A U91903 FRZB BG435302 EBF AF352728 FLJ12541 NM_005978 S100A2 BM128432 IGFBP5 NM_000900 MGP NM_003102 SOD3 AK026748 DKFZP761M1511 BE676272 TACC1 J03208 DBT AI692180 PPFIBP2 NM_002345 LUM AL544576 LOC92162 NM_006623 PHGDH NM_017688 BSPRY AF063606 my048 AU146310 N/A NM_001647 APOD AI912976 RASGRF2 AI935541 N/A U83508 ANGPT1 NM_005558 LAD1 L47125 GPC3 AW138125 PRODH2 NM_000663 ABAT

TABLE 10 Genes With Up-Regulated Expression In Benign Oncocytoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM_005114 HS3ST1 AF178532 BACE2 AA650558 GNAS AI521166 LOC283104 BF062244 LIN7A AA005023 NOD27 NM_030674 SLC38A1 AV725364 GPRC5B NM_014766 SCRN1 AW195581 GPSM2 BC002471 CPLX1 BG503479 B4GALT6 AF183421 RAB31 BF031829 DSG2 AK022100 KIAA0256 AW975728 SLC16A7 BF508244 AKR1C2 NM_022495 C14orf135 BG772511 N/A AA703159 N/A AB037848 SYT13 BF247552 SLC38A1 AK055769 N/A NM_001673 ASNS T58048 N/A NM_024622 FLJ21901 NM_012105 BACE2 AI565054 N/A AA992805 LEF1 AW058459 LOC134285 AK026420 DMN NM_001233 CAV2 NM_024812 BAALC BC036550 N/A AI057226 N/A BE464483 N/A AW138767 ELOVL7 NM_002512 NME2 NM_013233 STK39 AF178532 BACE2

TABLE 11 Genes With Down-Regulated Expression In Benign Oncocytoma Genbank ID Gene Symbol Genbank ID Gene Symbol BF593625 SYK AW274034 USP2 AI310001 FLJ22789 NM_147174 HS6ST2 NM_006206 PDGFRA AA074145 PRODH NM_003740 KCNK5 AL049176 CHRDL1 AW138125 PRODH2 NM_020353 PLSCR4 NM_000336 SCNN1B NM_024803 TUBAL3 BC005314 ALDOB D16931 ALB AI796189 PAH NM_019076 UGT1A10 NM_013363 PCOLCE2 AF138303 DCN NM_004466 GPC5 D13705 CYP4A11 AI627531 N/A NM_000587 C7 U28055 MSTP9 R49295 N/A NM_152759 MGC35140 NM_000385 AQP1 AW052159 N/A AI669229 RARRES1 NM_017712 PGPEP1 U36189 C5orf13 AI961231 TOX AL110135 FLJ14753 AI767962 BNC2 AW271605 N/A AF350881 TRPM6 BF358386 N/A AU146418 N/A NM_016270 KLF2 BE875072 N/A AA905508 LOC128153 AI653981 L1CAM NM_021630 PDLIM2 AI634662 SLC13A3 AA915989 TBC1D13 NM_000486 AQP2 AL565812 PTN AW206292 AQP2 AI990790 N/A AI572079 SNAI2 BC041158 CYP4A11 AI694118 N/A NM_138474 N/A NM_000142 FGFR3 NM_002899 RBP1 U78168 RAPGEF3 AK024256 KIAA1573 AI913600 UNQ846 AW779672 SLC17A1 W93847 MUC15 NM_021161 KCNK10 NM_004616 TM4SF3 BF196891 TPMT AI935789 UMOD AY028896 CARD10 NM_007180 TREH NM_018456 EAF2 AL110152 CD109 NM_017806 FLJ20406 AW051599 N/A X59065 FGF1 AI796169 GATA3 AI650353 DACH1 AF017987 SFRP1 AW771563 N/A BE550027 DKFZp761N1114 BF431313 N/A AA535065 KIAA1847 NM_000896 CYP4F3 NM_003361 UMOD BC005090 AGMAT AI263078 SLC23A3 U24267 ALDH4A1 M13149 HRG AI090268 N/A AF278532 NTN4 AW014927 CALB1 AI632015 SLC12A1 AL023553 PIPPIN NM_000412 HRG AL049313 N/A NM_000893 KNG1 AK021539 NCAG1 BG398937 KNG AI220117 MGST1 AL049977 CLDN8 NM_020300 MGST1 N74607 AQP3 NM_022568 ALDH8A1 AW071744 KCNJ10 BE874872 FAM20C AW015506 AQP2 NM_004668 MGAM AI927000 SOSTDC1 BF033242 CES2 AI471866 SLC7A13 BC004542 PLXNB2 NM_001099 ACPP NM_000204 F NM_005074 SLC17A1 NM_004525 LRP2 AA995925 N/A AA442149 MAF AF352728 FLJ12541 NM_000049 ASPA BF343007 TFAP2A AI830469 TFEC NM_016929 CLIC5 NM_003759 SLC4A4 AA911235 MST1 AF169017 FTCD AA639753 N/A AF170911 SLC23A1 NM_004887 CXCL14 AA865601 LOC123876 AW771565 AIM1 AA863031 MGC32871 AI264671 N/A AW136060 SLC13A2 BF510426 N/A NM_003041 SLC5A2 AV728958 TLN2 NM_021924 MUCDHL T90064 N/A AW299568 N/A AA218868 THY1 AI927941 N/A NM_003104 SORD AI433463 MME AJ292204 AGXT2 AL365347 SLC7A8 AI056359 MAPT AA502331 PRAP1 AL568422 DZIP1 NM_024709 FLJ14146 AF339805 N/A AF289024 FTCD NM_000163 GHR NM_017614 BHMT2 AI042017 NPL NM_016347 NAT8 AW340457 N/A NM_000277 PAH BF431199 DEHAL1 NM_000316 PTHR1 BF432254 MGC15937 NM_001091 ABP1 AI368018 GPD1 NM_000790 DDC AF144103 CXCL14 BF217861 MT1E NM_016725 FOLR1 BF447963 KIAA0962 NM_000050 ASS NM_001081 CUBN AA693817 N/A NM_018484 SLC22A11 NM_004929 CALB1 AW192692 N/A NM_000592 C4A BF000045 TINAG AL574184 HPGD BC005830 ANXA9 AA676742 DMGDH NM_025257 C6orf29 AI631993 N/A NM_020973 GBA3 AI566130 AK3 NM_001977 ENPEP AW024233 GLYAT AI632692 N/A AA873542 SLC6A19 BI825302 PR1 AK026966 AK3 L12468 ENPEP NM_022829 SLC13A3 AL571375 SCD4 NM_005950 MT1G AL136858 ZMYND12 AV700405 MGC52019 NM_024027 COLEC11 AI733515 MGC52019 NM_014934 DZIP1 NM_000860 HPGD BG496631 FBI4 U95090 PRODH2 NM_018265 FLJ10901 NM_001385 DPYS AI770035 UPB1 BG401568 SLC16A9 AF177272 UGT2B28 NM_000846 GSTA1 NM_004392 DACH1 BF195998 ALDOB N95363 CDKN1C NM_004413 DPEP1 AF261715 FOLH1 NM_000151 G6PC NM_000042 APOH NM_006744 RBP4 NM_001393 ECM2 NM_013410 AK3 R88990 N/A NM_000035 ALDOB AA557324 CYP4X1 AK026411 ALDOB AF116645 ALB AL135960 CYP4A11 BC015993 MGC27169 M74220 PLG AL558479 THY1 NM_001713 BHMT NM_000785 CYP27B1 AW614558 SLC39A5 AW051926 AMN Z92546 SUSD2 AA928708 CYP8B1 NM_000778 CYP4A11 BE407830 KIFC3 NM_000792 DIO1 AI431643 RRAS2 AI222435 N/A AF001434 EHD1 D26054 FBP1 BC005894 FMO2 AW025165 SLC22A8 NM_006798 UGT2A1 NM_007287 MME BF217861 MT1E

The following references were cited herein:

-   Copland et al., Recent Prog. Horm. Res. 58:25-53 (2003). -   Copland et al., Oncogene 22:8053-62 (2003). -   Grossman et al., J. Surg. Oncol. 28:237-244 (1985). -   Trifillis, Exp. Nephrol. 7:353-359 (1999). 

1. A method of detecting conventional or clear cell renal cell carcinoma, comprising the steps of: obtaining biological samples from an individual; determining gene expression level of one or more gene encoding one or more protein selected from the group consisting of TGF-β1, TGF-α, adrenomedulin, fibroblast growth factor 2 (FGF2), vascular epidermal growth factor (VEGF), osteonectin, follistatin like-3, inhibin beta A, spondin 2, chemokine X cytokine receptor 4 (CXCR4), fibronectin, neuropilin 1, frizzled homolog 1, insulin-like growth factor binding protein 3, laminin alpha 3, integrin beta 2, semaphorins 6A, semaphorins 5B, semaphorins 3B, caspase 1, sprouty 1, CDH16, PCDH9, compliment component 1-beta, compliment component 1-alpha, compliment component 1-gamma, CD53, CDW52, CD163, CD14, CD3Z, CD24, RAP1, angiopoietin 2, cytokine knot secreted protein, MAPKKKK4, 4-hydroxyphenylpyruvate dioxygenase, pyruvate carboxyknase 2, 11-beta-hydroxysteroid dehydrogenase 2, GAS1, CDKN1, nucleolar protein 3, interferon induced protein 44, NR3C1, vitamin D receptor, hypothetical protein FLJ14957 (Affy#225817_at), metallothionein 2A, metallothionein-If gene, metallothionein 1H, secreted frizzled related protein 1, connective tissue growth factor, and epidermal growth factor; and performing statistical analysis on the expression level of said gene as compared to that expressed in normal biological samples, wherein statistically different gene expression levels would indicate said individual has conventional or clear cell renal cell carcinoma.
 2. A method of detecting stage I or stage II conventional or clear cell renal cell carcinoma, comprising the steps of: obtaining biological samples from an individual; measuring in the biological samples an expression level of one or more genes in Tables 1, 3 or 5 or one or more genes in Tables 2, 4 or 6 or a combination thereof; and performing statistical analysis on the measured expression levels of the one or more genes as compared to that expressed in normal tissue samples, wherein over-expression of said one or more genes in Tables 1, 3 or 5 or under-expression of the one or more genes in Tables 2, 4 or 6 or a combination thereof indicates that said individual has stage I or I conventional or clear cell renal cell carcinoma.
 3. The method of claim 2, wherein the expression level is measured for one or more genes shown in one or both of Table 1 or Table 2 such that over-expression of the one or more genes in Table 1 or under-expression of the one or more genes in Table 2 or a combination thereof compared to the control is indicative of stage 1 conventional or clear cell renal cell carcinoma.
 4. The method of claim 3, wherein the expression level is measured in one or more of the genes shown in Table 1 such that over-expression of the one or more genes in compared to the control is indicative of stage I conventional or clear cell renal cell carcinoma.
 5. The method of claim 3, wherein the expression level is measured in one or more of the genes shown in Table 2 such that under-expression of the one or more genes in compared to the control is indicative of stage I conventional or clear cell renal cell carcinoma.
 6. The method of claim 2, wherein the expression level is measured for one or more genes shown in one or both of Table 3 or Table 4 such that over-expression of the one or more genes in Table 3 or under-expression of the one or more genes in Table 4 or a combination thereof compared to the control is indicative of stage II conventional or clear cell renal cell carcinoma.
 7. The method of claim 6, wherein the expression level is measured in one or more of the genes shown in Table 3 such that over-expression of the one or more genes in compared to the control is indicative of stage II conventional or clear cell renal cell carcinoma.
 8. The method of claim 6, wherein the expression level is measured in one or more of the genes shown in Table 4 such that under-expression of the one or more genes in compared to the control is indicative of stage II conventional or clear cell renal cell carcinoma.
 9. The method of claim 2, wherein the expression level is measured for one or more genes shown in one or both of Table 5 or Table 6 such that over-expression of the one or more genes in Table 5 or under-expression of the one or more genes in Table 6 or a combination thereof compared to the control is indicative of stage 1 or stage II conventional or clear cell renal cell carcinoma.
 10. The method of claim 9, wherein the expression level is measured in one or more of the genes shown in Table 5 such that over-expression of the one or more genes in compared to the control is indicative of stage I or stage II conventional or clear cell renal cell carcinoma.
 11. The method of claim 9, wherein the expression level is measured in one or more of the genes shown in Table 6 such that under-expression of the one or more genes in compared to the control is indicative of stage I or stage II conventional or clear cell renal cell carcinoma.
 12. The method of claim 2, said over-expression or said under-expression is at least 2 fold as compared to that expressed in normal tissue.
 13. A method of detecting stage I papillary renal cell carcinoma, comprising the steps of: obtaining biological samples from an individual; measuring in the biological samples an expression level of one or more genes in Table 8 or one or more genes in Table 9 or a combination thereof; and performing statistical analysis on the measured expression levels of the one or more genes as compared to that expressed in normal tissue samples, wherein over-expression of said one or more genes in Table 8 or under-expression of the one or more genes in Table 8 or a combination thereof indicates that said individual has stage I papillary renal cell carcinoma.
 14. The method of claim 13, wherein the expression level is measured in one or more of the genes shown in Table 8 such that over-expression of the one or more genes in compared to the control is indicative of stage I papillary renal cell carcinoma.
 15. The method of claim 13, wherein the expression level is measured in one or more of the genes shown in Table 9 such that under-expression of the one or more genes in compared to the control is indicative of stage I papillary renal cell carcinoma.
 16. The method of claim 13, wherein said over-expression or said under-expression is at least 2 fold as compared to that expressed in normal tissue.
 17. A method of detecting benign oncocytoma, comprising the steps of: obtaining biological samples from an individual; measuring in the biological samples an expression level of one or more genes in Table 10 or one or more genes in Table 11 or a combination thereof; and performing statistical analysis on the measured expression levels of the one or more genes as compared to that expressed in normal tissue samples, wherein over-expression of said one or more genes in Table 10 or under-expression of the one or more genes in Table 11 or a combination thereof indicates that said individual has stage I papillary renal cell carcinoma.
 18. The method of claim 17, wherein the expression level is measured in one or more of the genes shown in Table 10 such that over-expression of the one or more genes in compared to the control is indicative of benign oncocytoma.
 19. The method of claim 17, wherein the expression level is measured in one or more of the genes shown in Table 11 such that under-expression of the one or more genes in compared to the control is indicative of benign oncocytoma.
 20. The method of claim 17, wherein said over-expression or said under-expression is at least 2 fold as compared to that expressed in normal tissue. 